Quality-of-Content (QoC)-Driven Rate Allocation for Video Analysis in Mobile Surveillance Networks
|
|
- Paul Roberts
- 5 years ago
- Views:
Transcription
1 Quality-of-Content (QoC)-Diven Rate Allocation fo Video Analysis in Mobile Suveillance Netwoks Xiang Chen, Jenq-Neng Hwang, Kuan-Hui Lee, Ricado L. de Queioz Depatment of Electical Engineeing, Univesity of Washington, Seattle, WA 9895, USA. {xchen28, hwang, Depatment of Compute Science, Univesidade de Basilia, Basilia, Bazil. Abstact Nowadays, moe and moe videos ae tansmitted fo video analytics puposes athe than human peceptions. In mobile suveillance netwoks, a cloud seve collects videos deliveed fom multiple moving cameas and detects suspicious people in all the camea views. Howeve, all the videos ecoded by moving cameas such as phone o dash cameas ae uploaded though bandwidth-limited wieless netwoks. Theefoe, videos ae equied to be encoded with high compession atio to satisfy the total ate constaint, which may affect the video analyses (e.g., human detection/tacking and action ecognition, etc.) pefomance due to the degaded video decoding qualities at the seve side. In this pape, we popose an effective contentdiven video souce coding ate allocation scheme, which can impove the human detection success ate in mobile suveillance netwoks unde a total ate constaint. The poposed scheme allocates appopiate amount of ate to each moving camea based on the coesponding content infomation (i.e., human detection esults). A model of human detection accuacy based on object aea and video quality is povided. The ate allocation poblem is fomulated as a convex optimization poblem and can be solved by standad solves. Simulations with eal video sequences demonstate the effectiveness of ou poposed scheme. Keywods ate allocation; video analysis; human detection; visual suveillance; convex optimization I. INTRODUCTION The apidly inceasing demand of video steaming applications has boosted the development of wieless video tansmission technologies [], [2]. As pedicted in [3], 72 pecent of all consume mobile Intenet taffic will be mobile video in 29, up fom 55 pecent in 24. Futhemoe, mobile taffic will exponentially incease between 24 and 29, epesenting a 57 pecent of compound annual gowth ate (CAGR), which is about thee times faste than fixed IP taffic. Due to the bandwidth-limited natue of wieless channels, it is cucial to design efficient wieless video tansmission schemes fo the bandwidth-consuming eal-time video steaming sevices [4]. In taditional wieless video tansmission eseach, the optimization citeia ae eithe quality-of-sevice (QoS) based This study is conducted unde the 3-EC-7-A-3-S-24 poject fom the Ministy of Economic Affais (MOEA) of Taiwan and Advanced Wieless Boadband System and Inte-netwoking Application Technology Development Poject of the Institute fo Infomation Industy which is subsidized by the Ministy of Economy Affais of Taiwan. design [], o quality-of-expeience (QoE) based design [5] [9]. Fo QoS-based design, netwok paametes such as packet loss, delay, jitte, etc. ae jointly consideed in ode to impove the video steaming applications fom a netwok pespective. Fo QoE-based design, the use peception and expeience of decoded videos ae combined with the QoS paametes so that video tansmission paametes can be adjusted to impove uses satisfaction []. Both subjective and objective video quality measuements have been developed to quantify the QoE-based system design []. Although most of video tansmission sevices ae designed fo human peceptions, moe and moe video steaming ae collected fo video analytics puposes. In [2], authos developed a vehicle tacking system with static suveillance cameas. In [3], a live fish tacking system is developed based on low-contast and low-fame-ate steeo videos. Based on human detectos, pedestian tacking systems in single moving camea ae developed [4], [5]. Moeove, a system of onoad pedestian tacking acoss multiple diving ecodes fo mobile suveillance netwok is poposed in [6]. Most existing human-peception-based (QoE-based) wieless video tansmission designs may not be optimal fo video analytics puposes. Theefoe, it is necessay to develop moe efficient video tansmission schemes fo suveillance and compute vision applications. As intelligent suveillance systems become moe and moe impotant fo cime investigation and tagedy pevention, mobile suveillance netwoks with multiple moving cameas, which have moe flexible camea views compaing to taditional suveillance systems with static cameas, have thus been intoduced [6]. As indicated in [6], videos ae ecoded by diving ecodes (dash cameas) and uploaded to emote cloud seves fo futhe automatic analyses. Due to the mobility natue of moving cameas, wieless wide aea netwoks (WWAN) have to be used fo video tansmissions, whee efficient ate allocation is necessay because of the limited wieless esouces. Among diffeent applications in intelligent mobile suveillance netwoks, such as human tacking, action ecognition, behavio undestanding, etc., human detection is the fist step and its esult will citically affect the pefomance of othe
2 human-elated video analysis applications [6]. In [7], [8], image/video featues instead of the full video sequences ae uploaded to the cloud seves fo video analyses. Although tansmitting featues can save lots of wieless esouces, they ae not suitable fo suveillance puposes since the full video sequences ae equied to be achived in the seve fo futue investigations. In [9], authos poposed a saliency-based ate contol fo human detection with a single camea. Based on a popely designed saliency map, this scheme adaptively adjusts the quantization paametes (s) to peseve egions with small contast fom excessive smoothing so that the human detection accuacy can be impoved. In this pape, we popose a quality-of-content (QoC)-diven video souce coding ate allocation scheme fo human detection in the mobile suveillance netwoks with multiple moving cameas. Instead of consideing human peception in taditional video steaming design, the poposed scheme maximizes the oveall human detection accuacy at the emote seve when multiple moving cameas upload videos via WWAN with a total ate constaint. We analytically evaluate the factos that affect the pobability of successful human detections and popose a video souce coding ate allocation algoithm based on the human detection esults in the past goup of pictues (GoP). To the best of ou knowledge, thee is no existing QoCdiven wok conducted in video encoding ate allocation fo human detections in mobile suveillance system when multiple moving cameas compete fo the limited wieless esouces. The est of this pape is oganized as follows. In Section II, we will descibe the scenaio and system stuctue of mobile suveillance netwok. In Section III, evaluation of the factos that affect the successful human detections is povided. Section IV gives the poposed video souce coding ate adaptation algoithm. Simulation esults ae shown in Section V, followed by the conclusion emaks in Section VI. II. SCENARIOS AND SYSTEM STRUCTURE As shown in Fig., a mobile suveillance netwok consists of multiple moving cameas (mobile nodes) such as dash cameas and smatphone cameas, which ae andomly distibuted and moving aound in the aeas with diffeent pedestian densities. Each camea can encode and upload videos via a WWAN to a emote cloud seve in eal time fo futhe video analyses, such as human detection. The system stuctue is shown in Fig. 2, whee captued camea views ae encoded with the high efficiency video coding (HEVC) [2] with diffeent encoding ates. To educe the cost and computational complexity on each mobile node, human detection is pefomed in the cloud seve. Afte human detection is pefomed, an upload scheduling and esouce allocation module collects the human detection esults (contents) and assigns diffeent souce encoding ate taget to each camea. The oveall encoding ate is constained such that the tansmission can be bette suppoted by the netwok. Theefoe, the human detection accuacy is only elated to the souce coding ate allocation. In this wok, we assume all the video analyses ae conducted in the cloud seve. Not mobile node Video encode Human detection Mobile node Content info. seve wieless netwok Fig.. Scenaio of mobile suveillance netwok. Paamete estimation Video encode Human detection Mobile node Paamete estimation Wieless netwok Content info. Joint optimal ate allocation Video encode Human detection Cloud seve Fig. 2. Poposed system stuctue. Mobile node Paamete estimation mobile node Taget encoding ates Content info. only can it achive videos in the cloud seve fo futhe investigations, it can save computational cost and powe at mobile nodes as well, especially fo smatphone cameas. III. EFFECT OF VIDEO QUALITY ON HUMAN DETECTOR Many human detectos have been poposed in the liteatues. In [2], a human detecto, which can effectively epesent the shape of human, has been poposed based on the histogam of oiented gadient (HOG) featues. The implicit shape model (ISM) poposed in [22] applies a voting scheme based on multi-scale inteest points to ceate plenty of detection hypotheses, and a codebook is used to peseve the tained featues. The defomable pat model (DPM) [23], an extension of the idea in [2], uses a oot model and seveal pat models to descibe diffeent patitions of an object. Based on a pedefined geomety, the pat models ae spatially connected with the oot model so that the object can be pecisely depicted. Among diffeent human detectos, the DPM is a well-accepted obust and computational efficient scheme. Theefoe, we adopt the DPM as the human detection scheme in this pape. But simila concept can be applied to othe detection schemes. The DPM object detecto is based on HOG featues, which can be affected by the atifacts ceated fom video encode
3 Fig. 3. Human detection esult of DPM. Video clip: BAHNHOF in the ETHZ set [25]. Left: =5; Right: =39 Detection Accuacy x Object Aea (pixels) Fig. 4. Human detection accuacy with diffeent object aeas and s. with diffeent compession atios [9]. Theefoe, the eceived video quality will affect the detection pefomance in the cloud seve. Figue 3 shows a compaison of the DPM detection esults with two diffeent video encoding qualities in tems of diffeent s. When the video quality is poo, smalle objects in the view have lowe pobability to be successfully detected compaed to the lage objects in the view since a lage may smooth out the detailed shape infomation of smalle objects. Figue 4 illustates the human detection accuacy with diffeent object aeas (in tems of numbe of pixels) and s of HEVC encode [24]. Six video clips in ETHZ set [25] ae tested and each video is encoded with diffeent s fom 5 to 45. The detection esults ae compaed with the gound-tuth coodinate labels of each object in the set. If the ovelapped aea of the detection esult and the gound-tuth is lage than 5 pecent of the gound-tuth aea, the detected object is egaded as a successful detection [23]. The detection accuacy of a specific object aea a is calculated by counting all the tue-positive detected objects whose aeas ae lage than this specific value a and divided by the total numbe of objects whose aea is lage than this value a. Accoding to Fig. 4, the detection accuacy inceases with bette video fame quality (smalle ) and lage object aea. Suppose A is a andom vaiable epesenting the object BAHNHOF CROSSING LOEWENPLATZ x UW JELMOLI LINTHESCHER SUNNYDAY UW Fig. 5. Cuve-fitting esults of the souce encoding ate model in Eq. (2) with diffeent videos of VGA and 72p esolutions. aea, and Q is a andom vaiable epesenting. Due to the independence of A and Q, the detection accuacy in Fig. 4 can be expessed as: P A,Q (a, q) = f (A a) g (q), () whee f ( ) is the pobability of tue-positive detection esult when the objects aea is lage than a. g ( ) is the pobability of tue-positive detection esult as a function of video encoding q. In total 6 videos with VGA (64 48) esolution in ETHZ set [25] and 2 videos with 72p (28 72) esolution ecoded in the Univesity of Washington (UW) ae tested. We also investigate the human detection accuacy model by two-dimensional cuve-fitting in Fig. 5, Eq. () can be appoximated via egession as: P A,Q (a, q) = (.2865 exp ( a )) ( ).6 2 q/6 (2) The encoding ate model function (q) can also be epesented as a function of q. In this pape, we adopt a simple exponential model to fit the souce coding ate with espect to, i.e., (q) = c exp (c 2 q), (3) whee c and c 2 ae two paametes to be detemined. Figue 5 shows the elationship between diffeent and souce coding ate using HEVC encode. IV. PROPOSED VIDEO ENCODING RATE ALLOCATION SCHEME Since wieless video steaming is bandwidth consuming, and the oveall wieless esouce is limited in WWAN, it is
4 cucial to design an efficient ate allocation scheme so that the tue-positive detection esult is maximized unde a cetain total ate constaint. Theefoe, the objective of ou poposed system is to optimally allocate the video encoding ate of each mobile node unde a total ate constaint so that the oveall tue-positive detection pobability is maximized, i.e., max M N m n= P (a m,n, q m ( m )) m R (T) ; m R (min), m, whee M is the total numbe of mobile nodes. = [, 2,, M ] is the ate allocation vecto and the element m epesents the coesponding souce coding ate of the mobile node m. N m is the numbe of objects (people in human detection scenaio) in the view of mobile node m. R (T) is the total available ate of the system. R (min) is the minimum ate equiement so that the minimum detection capability can be maintained fo each mobile node. By taking the logaithm of the objective function, the optimization poblem in Eq. (4) can be efomulated as: max N m log (g (q m ( m )))+ N m n= m R (T) ; m R (min), m. log (f (a m,n )) In Eq. 5, the second tem of the objective function can be consideed as constant since the optimization vaiable only appeas in the fist tem. Theefoe, we emove the second tem so that the final poblem fomulation is: ( ) max N m log c (m) 2 log m c (m) m R (T) ; m R (min), m Note that in ou poblem fomulation, the optimal solution of the souce coding ate allocation is affected by human density indicated by N m. The objective function in Eq. (6) can be poven as a convex function [26] (see Appendix A). Since the constaint is linea, the optimization poblem in Eq. (6) becomes a convex optimization poblem, which can be effectively solved by existing tools such as CVX [27]. In ou implementation, the esouce allocation is updated in evey GoP time peiod and the human density N m is detemined by human detection esults in the last GoP time peiod. V. SIMULATION RESULTS The poposed algoithm is tested in this section. Thee video clips ae used to compete fo the limited wieless esouces: one video LINTHESCHER fom the ETHZ set [25] and two videos ecoded in UW campus. The esolutions and human densities of the thee videos ae listed in Table I. HEVC (4) (5) (6) TABLE I VIDEO RESOLUTIONS AND HUMAN DENSITIES Video Resolution Human Density UW Low UW Medium LINTHESCHER High Fig. 6. The sample fames of the thee videos. Left: UW ; Middle: UW 2 ; Right: LINTHESCHER. (X265 implementation) [24] is used as the video encode. The fame ate of each video is set as 25 fps. GoP sizes ae set as 6 fo all the videos. The encoding patten in each GoP block is one I-fame followed by 5 P-fames. 25 GoPs (4 fames) ae tested fo each video. The sample video fames of the thee videos ae shown in Fig. 6 We compae ou poposed QoC-diven ate allocation scheme with two othe schemes. One is the equal ate allocation scheme, which evenly allocates the total ate to each mobile node. The othe scheme is a distotion-diven ate allocation scheme, which ties to minimize the decoding meansquaed-eo (MSE) of the system. We adopt a ate-distotion model as [28]: d m () = c (m) 3 c(m) 4, (7) whee d m is the distotion in tems of MSE fo the mobile node m, while c (m) 3 and c (m) 4 ae two constants to be detemined. The MSE-diven ate allocation poblem can be expessed as: min d m ( m ) m R (T) ; m R (min), m. In the simulations, the minimum ate equiement R (min) fo ou poposed QoC-diven scheme and the MSE-diven ate allocation scheme ae both set as 2 Kbps. Figue 7 shows the souce coding ate allocation of these 3 videos when the total ate constaint is 4.8 Mbps. With the MSE-diven ate allocation scheme, the ate is allocated based on the distotion of each video, which is not diectly elated to human detection esults. Howeve, with the poposed QoC-diven ate allocation scheme, moe ate is allocated to the mobile nodes with highe human densities. Theefoe, the ate of the video clip LINTHESCHER is highe than that of UW 2 and the ate assigned to UW is the lowest. The pobabilities of total tue-positive detections with diffeent total ate constaints ae plotted in Fig. 8. With (8)
5 3 2 UW UW2 LINTHESCHER GoP index GoP index Pobability of false alams Poposed content diven MSE diven Equal Total ate constaint (Kbps) Fig. 7. Data ate allocation of the 3 videos with the poposed QoC-diven ate allocation scheme (top) and the MSE-diven ate allcoation scheme (bottom). Total ate constaint: 4.8 Mbps. Pobability of tue positive detections Poposed content diven MSE diven Equal Total ate constaint (Kbps) Fig. 8. Pobability of tue-positive human detections unde diffeent total ate constaints. moe available ate, the video encoding qualities become bette, esulting in impoving the tue-positive detection ates at the cloud seve. Moeove, with the same total ate constaint, the poposed QoC-diven ate allocation scheme has bette human detection pefomance compaing with the equal ate allocation scheme and the MSEdiven ate allocation scheme. It is noticeable that the MSE-diven ate allocation scheme has wose human detection pefomance than the equal ate allocation scheme. This indicates that tansmitting videos based on distotions (decoding qualities) may not be a suitable choice if the deliveed videos ae used fo video analysis othe than human peception. Also, the pefomance gain of the poposed QoC-diven scheme becomes less when the total available Fig. 9. False-alam ate unde diffeent total ate constaints. ate becomes highe. This is because of less video quality degadation with highe encoding ate. The human detecto may geneates some false-alam detections (i.e., no human exists in the egion of bounding box given by human detectos), which will cause poblems fo subsequent video analysis techniques based on human detections, such as human tacking, behavio undestanding, etc.. Theefoe, false-alam is anothe pefomance indicato fo human detections. Figue 9 shows the pobability of falsealams unde diffeent total ate constaints. Obviously, the false-alam ate becomes smalle when moe ate is available and high-quality videos ae decoded at the cloud seve. With the same total ate constaint, the poposed QoC-diven ate allocation scheme has the lowest falsealam ate. The videos of human detection esults ae available at QoC/ VI. CONCLUSIONS In this pape, we poposed a QoC-diven ate allocation scheme fo video analytics puposes in mobile suveillance netwok with multiple moving cameas. Unlike the taditional wieless video tansmission design fo human peception, ou poposed scheme ties to maximize the human detection ate. The DPM object detecto is used fo human detection and its accuacy model with espect to object aea and video quality is given. Ou poposed ate allocation scheme can be fomulated as a convex optimization poblem, which can be efficiently solved by existing solves. Simulation esults show the effectiveness of ou poposed scheme and its favoable pefomance compaing with equal ate allocation and MSEdiven ate allocation schemes. Plenty of futue woks can be conducted in both compute vision and video tansmission aeas. In compute vision aea, effects of video compession and tansmission eos on existing video analysis and compute gaphics technologies such
6 as object detection and tacking, pose and event ecognitions, 3-D scene econstuctions etc. can be investigated. While in video tansmission aea, it is necessay to develop noval video coding and tansmissions schemes, which can peseve the equied featues (e.g., [29]) fo existing compute vision technologies. As moe and moe videos ae tansmitted fo video analysis puposes, we believe that combining wieless video tansmission and compute vision techniques contains ich eseach topics and is cucial fo next geneation mobile netwoks based on the Intenet of things (IoT) and the big. APPENDIX A CONVEXITY OF THE OBJECTIVE FUNCTION IN EQ. (6) Let f (x) be defined as: f (x) = ( x log 6 c 2 c ), (9) which is convex with espect to x if c 2 is non-positive, and f 2 (x) is defined as: f 2 (x) =.6 2 x , () which is concave and non-inceasing with espect to x. By the composition ule [26], f 3 (x) = f 2 (f (x)) is concave. Similaly, since f 4 (x) = log (x) is concave and non-deceasing, f 5 (x) = f 4 (f 3 (x)) is also concave by the composition ule. Also, N m is the detection esult of mobile node m, which is non-negative. Theefoe, the objective function of Eq. (6) is a non-negative sum of concave functions f 5 ( m ), which is also concave [26]. REFERENCES [] J.-N. Hwang, Multimedia Netwoking: Fom Theoy to Pactice. Cambidge Univesity Pess, 29. [2] X. Chen, J.-N. Hwang, P.-H. Wu, H.-J. Su, and C.-N. Lee, Adaptive mode and modulation coding switching scheme in MIMO multicasting system, in Poc. of IEEE Intl. Symp. on Cicuits and Systems, Beijing, China, May [3] Cisco Visual Netwoking Index: Foecast and Methodology, 24-29, 25. [4] X. Chen, J.-N. Hwang, J. A. Ritcey, and C.-N. Lee, Quality-diven joint ate and powe adaptation fo scalable video tansmissions ove MIMO systems, submitted to IEEE Tans. on Cicuits and Systems fo Video Technologies, 25. [5] P.-H. Wu, C.-W. Huang, J.-N. Hwang, J. young Pyun, and J. Zhang, Video-quality-diven esouce allocation fo eal-time suveillance video uplinking ove OFDMA-based wieless netwoks, IEEE Tans. on Vehicula Tech., pp , 24. [6] X. Chen, J.-N. Hwang, C.-Y. Wang, and C.-N. Lee, A nea optimal QoE-diven powe allocation scheme fo SVC-based video tansmissions ove MIMO systems, in Poc. of IEEE Intl. Conf. on Communications, Sydney, NSW, June [7] X. Chen, J.-N. Hwang, C.-N. Lee, and S.-I. Chen, A nea optimal QoEdiven powe allocation scheme fo scalable video tansmissions ove MIMO systems, IEEE Jounal of Selected Topics in Signal Pocessing, vol. 9, no., pp , 25. [8] X. Chen, J.-N. Hwang, C.-J. Wu, S.-R. Yang, and C.-N. Lee, A QoEbased APP laye scheduling scheme fo scalable video tansmissions ove Multi-RAT systems, in Poc. of IEEE Intl. Conf. on Communications, London, UK, 25. [9] X. Chen, H. Du, J.-N. Hwang, J. A. Ritcey, and C.-N. Lee, A QoEdiven FEC ate adaptation scheme fo scalable video tansmissions ove MIMO systems, in Poc. of IEEE Intl. Conf. on Communications, London, UK, 25. [] M. Fiedle, T. Hossfeld, and P. Tan-Gia, A geneic quantitative elationship between quality of expeience and quality of sevice, Netwok, IEEE, vol. 24, no. 2, pp. 36 4, 2. [] A. K. Moothy, K. Seshadinathan, R. Soundaaajan, and A. C. Bovik, Wieless video quality assessment: A study of subjective scoes and objective algoithms, Cicuits and Systems fo Video Technology, IEEE Tansactions on, vol. 2, no. 4, pp , 2. [2] K.-H. Lee, J.-N. Hwang, and S.-I. Chen, Model-based vehicle localization based on thee-dimensional constained multiple-kenel tacking, IEEE Tans. on Cicuits and Systems fo Video Technology, vol. 25, no., pp. 38 5, 25. [3] M.-C. Chuang, J.-N. Hwang, K. Willianms, and R. Towle, Tacking live fish fom low-contast and low-fame-ate steeo videos, IEEE Tans. on Cicuits and Systems fo Video Technology, vol. 25, no., pp , 25. [4] K.-H. Lee, J.-N. Hwang, G. Okopal, and J. Pitton, Diving ecode based on-oad pedestian tacking using visual SLAM and constained multiple-kenel, in Poc. IEEE Intenational Conf. Intelligent Tanspotation System (ITSC), 24, pp [5] L. Hou, W. Wan, K.-H. Lee, J.-N. Hwang, G. Okopal, and J. Pitton, Defomable multiple-kenel based human tacking using a moving camea, in Poc. of IEEE Intl. Conf. on Acoustics, Speech, and Signal Pocessing (ICASSP), 25. [6] K.-H. Lee and J.-N. Hwang, On-oad pedestian tacking acoss multiple diving ecodes, IEEE Tans. on Multimedia, vol. 7, no. 9, pp , 25. [7] B. Giod, V. Chandasekha, D. M. Chen, N.-M. Cheung, R. Gzeszczuk, Y. Reznik, G. Takacs, S. S. Tsai, and R. Vedantham, Mobile visual seach, IEEE Signal Pocessing Magazine, vol. 28, no. 4, pp. 6 76, 2. [8] A. Redondi, M. Cesana, and M. Tagliasacchi, Rate-accuacy optimization in visual wieless senso netwoks, in Poc. of IEEE Intenational Confeence on Image Pocessing, 22, pp [9] S. Milani, R. Benadini, and R. Rinaldo, A saliency-based ate contol fo people detection in video, in Poc. of IEEE Intl. Conf. on Acoustics, Speech, and Signal Pocessing (ICASSP), 23, pp [2] G. J. Sullivan, J.-R. Ohm, W.-J. Han, and T. Wiegand, Oveview of the high efficiency video coding (HEVC) standad, IEEE Tans. on Cicuits and Systems fo Video Technology, vol. 22, no. 2, pp , 22. [2] N. Dalal and B. Tiggs, Histogams of oiented gadients fo human detection, in Poc. of IEEE Compute Society Conf. on Compute Vision and Patten Recognition (CVPR). IEEE, 25, pp [22] B. Leibe, A. Leonadis, and B. Schiele, Robust object detection with inteleaved categoization and segmentation, Intenational jounal of compute vision, vol. 77, no. -3, pp , 28. [23] P. F. Felzenszwalb, R. B. Gishick, D. McAlleste, and D. Ramanan, Object detection with disciminatively tained pat-based models, Patten Analysis and Machine Intelligence, IEEE Tansactions on, vol. 32, no. 9, pp , 2. [24] The X265 website. [Online]. Available at [25] A. Ess, B. Leibe, K. Schindle, and L. V. Gool, A mobile vision system fo obust multi-peson tacking, in Poc. of IEEE Compute Society Conf. on Compute Vision and Patten Recognition (CVPR). IEEE, 28, pp. 8. [26] S. Boyd and L. Vandenbeghe, Convex Optimization. Cambidge Univesity Pess, 24. [27] M. Gant and S. Boyd. CVX: MATLAB softwae fo disciplined convex pogamming. [Online]. Available at boyd/cvx. [28] Y.-H. Huang, T.-S. Ou, P.-Y. Su, and H. H. Chen, Peceptual atedistotion optimization using stuctual similaity index as quality metic, IEEE Tans. on Cicuits and Systems fo Video Technology, vol. 2, no., pp , 2. [29] J. Chao, R. Huitl, E. Steinbach, and D. Schoede, A novel ate contol famewok fo sift/suf featue pesevation in h. 264/avc video compession, IEEE Tans. on Cicuits and Systems fo Video Technology, vol. 25, no. 6, pp , 24.
IP Network Design by Modified Branch Exchange Method
Received: June 7, 207 98 IP Netwok Design by Modified Banch Method Kaiat Jaoenat Natchamol Sichumoenattana 2* Faculty of Engineeing at Kamphaeng Saen, Kasetsat Univesity, Thailand 2 Faculty of Management
More informationColor Correction Using 3D Multiview Geometry
Colo Coection Using 3D Multiview Geomety Dong-Won Shin and Yo-Sung Ho Gwangju Institute of Science and Technology (GIST) 13 Cheomdan-gwagio, Buk-ku, Gwangju 500-71, Republic of Koea ABSTRACT Recently,
More informationDetection and Recognition of Alert Traffic Signs
Detection and Recognition of Alet Taffic Signs Chia-Hsiung Chen, Macus Chen, and Tianshi Gao 1 Stanfod Univesity Stanfod, CA 9305 {echchen, macuscc, tianshig}@stanfod.edu Abstact Taffic signs povide dives
More informationA Two-stage and Parameter-free Binarization Method for Degraded Document Images
A Two-stage and Paamete-fee Binaization Method fo Degaded Document Images Yung-Hsiang Chiu 1, Kuo-Liang Chung 1, Yong-Huai Huang 2, Wei-Ning Yang 3, Chi-Huang Liao 4 1 Depatment of Compute Science and
More informationJournal of World s Electrical Engineering and Technology J. World. Elect. Eng. Tech. 1(1): 12-16, 2012
2011, Scienceline Publication www.science-line.com Jounal of Wold s Electical Engineeing and Technology J. Wold. Elect. Eng. Tech. 1(1): 12-16, 2012 JWEET An Efficient Algoithm fo Lip Segmentation in Colo
More informationControlled Information Maximization for SOM Knowledge Induced Learning
3 Int'l Conf. Atificial Intelligence ICAI'5 Contolled Infomation Maximization fo SOM Knowledge Induced Leaning Ryotao Kamimua IT Education Cente and Gaduate School of Science and Technology, Tokai Univeisity
More informationAn Unsupervised Segmentation Framework For Texture Image Queries
An Unsupevised Segmentation Famewok Fo Textue Image Queies Shu-Ching Chen Distibuted Multimedia Infomation System Laboatoy School of Compute Science Floida Intenational Univesity Miami, FL 33199, USA chens@cs.fiu.edu
More informationPositioning of a robot based on binocular vision for hand / foot fusion Long Han
2nd Intenational Confeence on Advances in Mechanical Engineeing and Industial Infomatics (AMEII 26) Positioning of a obot based on binocula vision fo hand / foot fusion Long Han Compute Science and Technology,
More informationSlotted Random Access Protocol with Dynamic Transmission Probability Control in CDMA System
Slotted Random Access Potocol with Dynamic Tansmission Pobability Contol in CDMA System Intaek Lim 1 1 Depatment of Embedded Softwae, Busan Univesity of Foeign Studies, itlim@bufs.ac.k Abstact In packet
More informationOptical Flow for Large Motion Using Gradient Technique
SERBIAN JOURNAL OF ELECTRICAL ENGINEERING Vol. 3, No. 1, June 2006, 103-113 Optical Flow fo Lage Motion Using Gadient Technique Md. Moshaof Hossain Sake 1, Kamal Bechkoum 2, K.K. Islam 1 Abstact: In this
More informationA Novel Automatic White Balance Method For Digital Still Cameras
A Novel Automatic White Balance Method Fo Digital Still Cameas Ching-Chih Weng 1, Home Chen 1,2, and Chiou-Shann Fuh 3 Depatment of Electical Engineeing, 2 3 Gaduate Institute of Communication Engineeing
More informationA modal estimation based multitype sensor placement method
A modal estimation based multitype senso placement method *Xue-Yang Pei 1), Ting-Hua Yi 2) and Hong-Nan Li 3) 1),)2),3) School of Civil Engineeing, Dalian Univesity of Technology, Dalian 116023, China;
More informationPoint-Biserial Correlation Analysis of Fuzzy Attributes
Appl Math Inf Sci 6 No S pp 439S-444S (0 Applied Mathematics & Infomation Sciences An Intenational Jounal @ 0 NSP Natual Sciences Publishing o Point-iseial oelation Analysis of Fuzzy Attibutes Hao-En hueh
More informationModule 6 STILL IMAGE COMPRESSION STANDARDS
Module 6 STILL IMAE COMPRESSION STANDARDS Lesson 17 JPE-2000 Achitectue and Featues Instuctional Objectives At the end of this lesson, the students should be able to: 1. State the shotcomings of JPE standad.
More informationSegmentation of Casting Defects in X-Ray Images Based on Fractal Dimension
17th Wold Confeence on Nondestuctive Testing, 25-28 Oct 2008, Shanghai, China Segmentation of Casting Defects in X-Ray Images Based on Factal Dimension Jue WANG 1, Xiaoqin HOU 2, Yufang CAI 3 ICT Reseach
More informationA ROI Focusing Mechanism for Digital Cameras
A ROI Focusing Mechanism fo Digital Cameas Chu-Hui Lee, Meng-Feng Lin, Chun-Ming Huang, and Chun-Wei Hsu Abstact With the development and application of digital technologies, the digital camea is moe popula
More informationFrequency Domain Approach for Face Recognition Using Optical Vanderlugt Filters
Optics and Photonics Jounal, 016, 6, 94-100 Published Online August 016 in SciRes. http://www.scip.og/jounal/opj http://dx.doi.og/10.436/opj.016.68b016 Fequency Domain Appoach fo Face Recognition Using
More informationAn Assessment of the Efficiency of Close-Range Photogrammetry for Developing a Photo-Based Scanning Systeminthe Shams Tabrizi Minaret in Khoy City
Austalian Jounal of Basic and Applied Sciences, 5(1): 80-85, 011 ISSN 1991-8178 An Assessment of the Efficiency of Close-Range Photogammety fo Developing a Photo-Based Scanning Systeminthe Shams Tabizi
More informationCommunication vs Distributed Computation: an alternative trade-off curve
Communication vs Distibuted Computation: an altenative tade-off cuve Yahya H. Ezzeldin, Mohammed amoose, Chistina Fagouli Univesity of Califonia, Los Angeles, CA 90095, USA, Email: {yahya.ezzeldin, mkamoose,
More informationPerformance Optimization in Structured Wireless Sensor Networks
5 The Intenational Aab Jounal of Infomation Technology, Vol. 6, o. 5, ovembe 9 Pefomance Optimization in Stuctued Wieless Senso etwoks Amine Moussa and Hoda Maalouf Compute Science Depatment, ote Dame
More informationIllumination methods for optical wear detection
Illumination methods fo optical wea detection 1 J. Zhang, 2 P.P.L.Regtien 1 VIMEC Applied Vision Technology, Coy 43, 5653 LC Eindhoven, The Nethelands Email: jianbo.zhang@gmail.com 2 Faculty Electical
More informationAN ANALYSIS OF COORDINATED AND NON-COORDINATED MEDIUM ACCESS CONTROL PROTOCOLS UNDER CHANNEL NOISE
AN ANALYSIS OF COORDINATED AND NON-COORDINATED MEDIUM ACCESS CONTROL PROTOCOLS UNDER CHANNEL NOISE Tolga Numanoglu, Bulent Tavli, and Wendi Heinzelman Depatment of Electical and Compute Engineeing Univesity
More informationAdaptation of TDMA Parameters Based on Network Conditions
Adaptation of TDMA Paametes Based on Netwok Conditions Boa Kaaoglu Dept. of Elect. and Compute Eng. Univesity of Rocheste Rocheste, NY 14627 Email: kaaoglu@ece.ocheste.edu Tolga Numanoglu Dept. of Elect.
More informationModelling, simulation, and performance analysis of a CAN FD system with SAE benchmark based message set
Modelling, simulation, and pefomance analysis of a CAN FD system with SAE benchmak based message set Mahmut Tenuh, Panagiotis Oikonomidis, Peiklis Chachalakis, Elias Stipidis Mugla S. K. Univesity, TR;
More informationHISTOGRAMS are an important statistic reflecting the
JOURNAL OF L A T E X CLASS FILES, VOL. 14, NO. 8, AUGUST 2015 1 D 2 HistoSketch: Disciminative and Dynamic Similaity-Peseving Sketching of Steaming Histogams Dingqi Yang, Bin Li, Laua Rettig, and Philippe
More informationPrioritized Traffic Recovery over GMPLS Networks
Pioitized Taffic Recovey ove GMPLS Netwoks 2005 IEEE. Pesonal use of this mateial is pemitted. Pemission fom IEEE mu be obtained fo all othe uses in any cuent o futue media including epinting/epublishing
More informationA New Finite Word-length Optimization Method Design for LDPC Decoder
A New Finite Wod-length Optimization Method Design fo LDPC Decode Jinlei Chen, Yan Zhang and Xu Wang Key Laboatoy of Netwok Oiented Intelligent Computation Shenzhen Gaduate School, Habin Institute of Technology
More informationADDING REALISM TO SOURCE CHARACTERIZATION USING A GENETIC ALGORITHM
ADDING REALISM TO SOURCE CHARACTERIZATION USING A GENETIC ALGORITHM Luna M. Rodiguez*, Sue Ellen Haupt, and Geoge S. Young Depatment of Meteoology and Applied Reseach Laboatoy The Pennsylvania State Univesity,
More informationTowards Adaptive Information Merging Using Selected XML Fragments
Towads Adaptive Infomation Meging Using Selected XML Fagments Ho-Lam Lau and Wilfed Ng Depatment of Compute Science and Engineeing, The Hong Kong Univesity of Science and Technology, Hong Kong {lauhl,
More informationVoting-Based Grouping and Interpretation of Visual Motion
Voting-Based Gouping and Intepetation of Visual Motion Micea Nicolescu Depatment of Compute Science Univesity of Nevada, Reno Reno, NV 89557 micea@cs.un.edu Géad Medioni Integated Media Systems Cente Univesity
More informationIP Multicast Simulation in OPNET
IP Multicast Simulation in OPNET Xin Wang, Chien-Ming Yu, Henning Schulzinne Paul A. Stipe Columbia Univesity Reutes Depatment of Compute Science 88 Pakway Dive South New Yok, New Yok Hauppuage, New Yok
More informationImage Enhancement in the Spatial Domain. Spatial Domain
8-- Spatial Domain Image Enhancement in the Spatial Domain What is spatial domain The space whee all pixels fom an image In spatial domain we can epesent an image by f( whee x and y ae coodinates along
More informationImage Registration among UAV Image Sequence and Google Satellite Image Under Quality Mismatch
0 th Intenational Confeence on ITS Telecommunications Image Registation among UAV Image Sequence and Google Satellite Image Unde Quality Mismatch Shih-Ming Huang and Ching-Chun Huang Depatment of Electical
More informationINFORMATION DISSEMINATION DELAY IN VEHICLE-TO-VEHICLE COMMUNICATION NETWORKS IN A TRAFFIC STREAM
INFORMATION DISSEMINATION DELAY IN VEHICLE-TO-VEHICLE COMMUNICATION NETWORKS IN A TRAFFIC STREAM LiLi Du Depatment of Civil, Achitectual, and Envionmental Engineeing Illinois Institute of Technology 3300
More informationOn the Forwarding Area of Contention-Based Geographic Forwarding for Ad Hoc and Sensor Networks
On the Fowading Aea of Contention-Based Geogaphic Fowading fo Ad Hoc and Senso Netwoks Dazhi Chen Depatment of EECS Syacuse Univesity Syacuse, NY dchen@sy.edu Jing Deng Depatment of CS Univesity of New
More informationSYSTEM LEVEL REUSE METRICS FOR OBJECT ORIENTED SOFTWARE : AN ALTERNATIVE APPROACH
I J C A 7(), 202 pp. 49-53 SYSTEM LEVEL REUSE METRICS FOR OBJECT ORIENTED SOFTWARE : AN ALTERNATIVE APPROACH Sushil Goel and 2 Rajesh Vema Associate Pofesso, Depatment of Compute Science, Dyal Singh College,
More informationA Memory Efficient Array Architecture for Real-Time Motion Estimation
A Memoy Efficient Aay Achitectue fo Real-Time Motion Estimation Vasily G. Moshnyaga and Keikichi Tamau Depatment of Electonics & Communication, Kyoto Univesity Sakyo-ku, Yoshida-Honmachi, Kyoto 66-1, JAPAN
More informationDynamic Topology Control to Reduce Interference in MANETs
Dynamic Topology Contol to Reduce Intefeence in MANETs Hwee Xian TAN 1,2 and Winston K. G. SEAH 2,1 {stuhxt, winston}@i2.a-sta.edu.sg 1 Depatment of Compute Science, School of Computing, National Univesity
More informationA Recommender System for Online Personalization in the WUM Applications
A Recommende System fo Online Pesonalization in the WUM Applications Mehdad Jalali 1, Nowati Mustapha 2, Ali Mamat 2, Md. Nasi B Sulaiman 2 Abstact foeseeing of use futue movements and intentions based
More informationObstacle Avoidance of Autonomous Mobile Robot using Stereo Vision Sensor
Obstacle Avoidance of Autonomous Mobile Robot using Steeo Vision Senso Masako Kumano Akihisa Ohya Shin ichi Yuta Intelligent Robot Laboatoy Univesity of Tsukuba, Ibaaki, 35-8573 Japan E-mail: {masako,
More informationA Cross-Layer Framework of QoS Routing and Distributed Scheduling for Mesh Networks
A Coss-Laye Famewok of QoS Routing and Distibuted Scheduling fo Mesh Netwoks Chi Haold Liu, Athanasios Gkelias, and Kin K. Leung Depatment of Electical and Electonic Engineeing, Impeial College London
More informationTransmission Lines Modeling Based on Vector Fitting Algorithm and RLC Active/Passive Filter Design
Tansmission Lines Modeling Based on Vecto Fitting Algoithm and RLC Active/Passive Filte Design Ahmed Qasim Tuki a,*, Nashien Fazilah Mailah b, Mohammad Lutfi Othman c, Ahmad H. Saby d Cente fo Advanced
More informationLecture # 04. Image Enhancement in Spatial Domain
Digital Image Pocessing CP-7008 Lectue # 04 Image Enhancement in Spatial Domain Fall 2011 2 domains Spatial Domain : (image plane) Techniques ae based on diect manipulation of pixels in an image Fequency
More informationScaling Location-based Services with Dynamically Composed Location Index
Scaling Location-based Sevices with Dynamically Composed Location Index Bhuvan Bamba, Sangeetha Seshadi and Ling Liu Distibuted Data Intensive Systems Laboatoy (DiSL) College of Computing, Geogia Institute
More informationAn Improved Resource Reservation Protocol
Jounal of Compute Science 3 (8: 658-665, 2007 SSN 549-3636 2007 Science Publications An mpoved Resouce Resevation Potocol Desie Oulai, Steven Chambeland and Samuel Piee Depatment of Compute Engineeing
More informationA New and Efficient 2D Collision Detection Method Based on Contact Theory Xiaolong CHENG, Jun XIAO a, Ying WANG, Qinghai MIAO, Jian XUE
5th Intenational Confeence on Advanced Mateials and Compute Science (ICAMCS 2016) A New and Efficient 2D Collision Detection Method Based on Contact Theoy Xiaolong CHENG, Jun XIAO a, Ying WANG, Qinghai
More informationDesired Attitude Angles Design Based on Optimization for Side Window Detection of Kinetic Interceptor *
Poceedings of the 7 th Chinese Contol Confeence July 6-8, 008, Kunming,Yunnan, China Desied Attitude Angles Design Based on Optimization fo Side Window Detection of Kinetic Intecepto * Zhu Bo, Quan Quan,
More informationA VECTOR PERTURBATION APPROACH TO THE GENERALIZED AIRCRAFT SPARE PARTS GROUPING PROBLEM
Accepted fo publication Intenational Jounal of Flexible Automation and Integated Manufactuing. A VECTOR PERTURBATION APPROACH TO THE GENERALIZED AIRCRAFT SPARE PARTS GROUPING PROBLEM Nagiza F. Samatova,
More informationTopological Characteristic of Wireless Network
Topological Chaacteistic of Wieless Netwok Its Application to Node Placement Algoithm Husnu Sane Naman 1 Outline Backgound Motivation Papes and Contibutions Fist Pape Second Pape Thid Pape Futue Woks Refeences
More informationWIRELESS sensor networks (WSNs), which are capable
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, VOL. XX, NO. XX, XXX 214 1 Lifetime and Enegy Hole Evolution Analysis in Data-Gatheing Wieless Senso Netwoks Ju Ren, Student Membe, IEEE, Yaoxue Zhang, Kuan
More informationBo Gu and Xiaoyan Hong*
Int. J. Ad Hoc and Ubiquitous Computing, Vol. 11, Nos. /3, 1 169 Tansition phase of connectivity fo wieless netwoks with gowing pocess Bo Gu and Xiaoyan Hong* Depatment of Compute Science, Univesity of
More informationXFVHDL: A Tool for the Synthesis of Fuzzy Logic Controllers
XFVHDL: A Tool fo the Synthesis of Fuzzy Logic Contolles E. Lago, C. J. Jiménez, D. R. López, S. Sánchez-Solano and A. Baiga Instituto de Micoelectónica de Sevilla. Cento Nacional de Micoelectónica, Edificio
More informationErasure-Coding Based Routing for Opportunistic Networks
Easue-Coding Based Routing fo Oppotunistic Netwoks Yong Wang, Sushant Jain, Magaet Matonosi, Kevin Fall Pinceton Univesity, Univesity of Washington, Intel Reseach Bekeley ABSTRACT Routing in Delay Toleant
More informationHierarchically Clustered P2P Streaming System
Hieachically Clusteed P2P Steaming System Chao Liang, Yang Guo, and Yong Liu Polytechnic Univesity Thomson Lab Booklyn, NY 11201 Pinceton, NJ 08540 Abstact Pee-to-pee video steaming has been gaining populaity.
More informationTier-Based Underwater Acoustic Routing for Applications with Reliability and Delay Constraints
Tie-Based Undewate Acoustic Routing fo Applications with Reliability and Delay Constaints Li-Chung Kuo Depatment of Electical Engineeing State Univesity of New Yok at Buffalo Buffalo, New Yok 14260 Email:
More informationView Synthesis using Depth Map for 3D Video
View Synthesis using Depth Map fo 3D Video Cheon Lee and Yo-Sung Ho Gwangju Institute of Science and Technology (GIST) 1 Oyong-dong, Buk-gu, Gwangju, 500-712, Republic of Koea E-mail: {leecheon, hoyo}@gist.ac.k
More informationCellular Neural Network Based PTV
3th Int Symp on Applications of Lase Techniques to Fluid Mechanics Lisbon, Potugal, 6-9 June, 006 Cellula Neual Netwok Based PT Kazuo Ohmi, Achyut Sapkota : Depatment of Infomation Systems Engineeing,
More informationFast quality-guided flood-fill phase unwrapping algorithm for three-dimensional fringe pattern profilometry
Univesity of Wollongong Reseach Online Faculty of Infomatics - Papes (Achive) Faculty of Engineeing and Infomation Sciences 2010 Fast quality-guided flood-fill phase unwapping algoithm fo thee-dimensional
More informationFifth Wheel Modelling and Testing
Fifth heel Modelling and Testing en Masoy Mechanical Engineeing Depatment Floida Atlantic Univesity Boca aton, FL 4 Lois Malaptias IFMA Institut Fancais De Mechanique Advancee ampus De lemont Feand Les
More informationMulti-azimuth Prestack Time Migration for General Anisotropic, Weakly Heterogeneous Media - Field Data Examples
Multi-azimuth Pestack Time Migation fo Geneal Anisotopic, Weakly Heteogeneous Media - Field Data Examples S. Beaumont* (EOST/PGS) & W. Söllne (PGS) SUMMARY Multi-azimuth data acquisition has shown benefits
More informationOn using circuit-switched networks for file transfers
On using cicuit-switched netwoks fo file tansfes Xiuduan Fang, Malathi Veeaaghavan Univesity of Viginia Email: {xf4c, mv5g}@viginia.edu Abstact High-speed optical cicuit-switched netwoks ae being deployed
More informationTime-Constrained Big Data Transfer for SDN-Enabled Smart City
Emeging Tends, Issues, and Challenges in Big Data and Its Implementation towad Futue Smat Cities Time-Constained Big Data Tansfe fo SDN-Enabled Smat City Yuanguo Bi, Chuan Lin, Haibo Zhou, Peng Yang, Xuemin
More informationLifetime and Energy Hole Evolution Analysis in Data-Gathering Wireless Sensor Networks
788 IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, VOL. 12, NO. 2, APRIL 2016 Lifetime and Enegy Hole Evolution Analysis in Data-Gatheing Wieless Senso Netwoks Ju Ren, Student Membe, IEEE, Yaoxue Zhang,
More informationCardiac C-Arm CT. SNR Enhancement by Combining Multiple Retrospectively Motion Corrected FDK-Like Reconstructions
Cadiac C-Am CT SNR Enhancement by Combining Multiple Retospectively Motion Coected FDK-Like Reconstuctions M. Pümme 1, L. Wigstöm 2,3, R. Fahig 2, G. Lauitsch 4, J. Honegge 1 1 Institute of Patten Recognition,
More informationThe Dual Round Robin Matching Switch with Exhaustive Service
The Dual Round Robin Matching Switch with Exhaustive Sevice Yihan Li, Shivenda S. Panwa, H. Jonathan Chao Abstact Vitual Output Queuing is widely used by fixed-length highspeed switches to ovecome head-of-line
More informationA Neural Network Model for Storing and Retrieving 2D Images of Rotated 3D Object Using Principal Components
A Neual Netwok Model fo Stong and Reteving 2D Images of Rotated 3D Object Using Pncipal Components Tsukasa AMANO, Shuichi KUROGI, Ayako EGUCHI, Takeshi NISHIDA, Yasuhio FUCHIKAWA Depatment of Contol Engineeng,
More informationSpiral Recognition Methodology and Its Application for Recognition of Chinese Bank Checks
Spial Recognition Methodology and Its Application fo Recognition of Chinese Bank Checks Hanshen Tang 1, Emmanuel Augustin 2, Ching Y. Suen 1, Olivie Baet 2, Mohamed Cheiet 3 1 Cente fo Patten Recognition
More informationImproved Fourier-transform profilometry
Impoved Fouie-tansfom pofilomety Xianfu Mao, Wenjing Chen, and Xianyu Su An impoved optical geomety of the pojected-finge pofilomety technique, in which the exit pupil of the pojecting lens and the entance
More informationAn Extension to the Local Binary Patterns for Image Retrieval
, pp.81-85 http://x.oi.og/10.14257/astl.2014.45.16 An Extension to the Local Binay Pattens fo Image Retieval Zhize Wu, Yu Xia, Shouhong Wan School of Compute Science an Technology, Univesity of Science
More informationEffects of Model Complexity on Generalization Performance of Convolutional Neural Networks
Effects of Model Complexity on Genealization Pefomance of Convolutional Neual Netwoks Tae-Jun Kim 1, Dongsu Zhang 2, and Joon Shik Kim 3 1 Seoul National Univesity, Seoul 151-742, Koea, E-mail: tjkim@bi.snu.ac.k
More informationDISTRIBUTION MIXTURES
Application Example 7 DISTRIBUTION MIXTURES One fequently deals with andom vaiables the distibution of which depends on vaious factos. One example is the distibution of atmospheic paametes such as wind
More informationMobility Pattern Recognition in Mobile Ad-Hoc Networks
Mobility Patten Recognition in Mobile Ad-Hoc Netwoks S. M. Mousavi Depatment of Compute Engineeing, Shaif Univesity of Technology sm_mousavi@ce.shaif.edu H. R. Rabiee Depatment of Compute Engineeing, Shaif
More informationAnalysis of Wired Short Cuts in Wireless Sensor Networks
Analysis of Wied Shot Cuts in Wieless Senso Netwos ohan Chitaduga Depatment of Electical Engineeing, Univesity of Southen Califonia, Los Angeles 90089, USA Email: chitadu@usc.edu Ahmed Helmy Depatment
More informationAPPLICATION OF STRUCTURED QUEUING NETWORKS IN QOS ESTIMITION OF TELECOMMUNICATION SERVICE
APPLICATION OF STRUCTURED QUEUING NETWORKS IN QOS ESTIMITION OF TELECOMMUNICATION SERVICE 1 YAROSLAVTSEV A.F., 2 Al-THUNEIBAT S.A., 3 AL TAWALBEH N.A 1 Depatment of Netwoking, SSUTI, Novosibisk, Russia
More informationA Minutiae-based Fingerprint Matching Algorithm Using Phase Correlation
A Minutiae-based Fingepint Matching Algoithm Using Phase Coelation Autho Chen, Weiping, Gao, Yongsheng Published 2007 Confeence Title Digital Image Computing: Techniques and Applications DOI https://doi.og/10.1109/dicta.2007.4426801
More informationTopic -3 Image Enhancement
Topic -3 Image Enhancement (Pat 1) DIP: Details Digital Image Pocessing Digital Image Chaacteistics Spatial Spectal Gay-level Histogam DFT DCT Pe-Pocessing Enhancement Restoation Point Pocessing Masking
More informationSCALABLE ENERGY EFFICIENT AD-HOC ON DEMAND DISTANCE VECTOR (SEE-AODV) ROUTING PROTOCOL IN WIRELESS MESH NETWORKS
SCALABL NRGY FFICINT AD-HOC ON DMAND DISTANC VCTOR (S-AODV) ROUTING PROTOCOL IN WIRLSS MSH NTWORKS Sikande Singh Reseach Schola, Depatment of Compute Science & ngineeing, Punjab ngineeing College (PC),
More informationNumber of Paths and Neighbours Effect on Multipath Routing in Mobile Ad Hoc Networks
Numbe of Paths and Neighbous Effect on Multipath Routing in Mobile Ad Hoc Netwoks Oday Jeew School of Infomation Systems and Accounting Univesity of Canbea Canbea ACT 2617, Austalia oday.jeew@canbea.edu.au
More informationThe concept of PARPS - Packet And Resource Plan Scheduling
The concept of PARPS - Packet And Resouce Plan Scheduling Magnus Eiksson 1 and Håkan Sätebeg 2 1) Dept. of Signals, Sensos and Systems, Royal Inst. of Technology, Sweden. E-mail: magnus.eiksson@ite.mh.se.
More informationA Full-mode FME VLSI Architecture Based on 8x8/4x4 Adaptive Hadamard Transform For QFHD H.264/AVC Encoder
20 IEEE/IFIP 9th Intenational Confeence on VLSI and System-on-Chip A Full-mode FME VLSI Achitectue Based on 8x8/ Adaptive Hadamad Tansfom Fo QFHD H264/AVC Encode Jialiang Liu, Xinhua Chen College of Infomation
More informationRT-WLAN: A Soft Real-Time Extension to the ORiNOCO Linux Device Driver
1 RT-WLAN: A Soft Real-Time Extension to the ORiNOCO Linux Device Dive Amit Jain Daji Qiao Kang G. Shin The Univesity of Michigan Ann Abo, MI 4819, USA {amitj,dqiao,kgshin@eecs.umich.edu Abstact The cuent
More informationa Not yet implemented in current version SPARK: Research Kit Pointer Analysis Parameters Soot Pointer analysis. Objectives
SPARK: Soot Reseach Kit Ondřej Lhoták Objectives Spak is a modula toolkit fo flow-insensitive may points-to analyses fo Java, which enables expeimentation with: vaious paametes of pointe analyses which
More informationUser Group testing report
Use Goup testing epot Deliveable No: D6.10 Contact No: Integated Poject No. 506723: SafetyNet Aconym: SafetyNet Title: Building the Euopean Road Safety Obsevatoy Integated Poject, Thematic Pioity 6.2 Sustainable
More informationANALYTIC PERFORMANCE MODELS FOR SINGLE CLASS AND MULTIPLE CLASS MULTITHREADED SOFTWARE SERVERS
ANALYTIC PERFORMANCE MODELS FOR SINGLE CLASS AND MULTIPLE CLASS MULTITHREADED SOFTWARE SERVERS Daniel A Menascé Mohamed N Bennani Dept of Compute Science Oacle, Inc Geoge Mason Univesity 1211 SW Fifth
More informationExtract Object Boundaries in Noisy Images using Level Set. Final Report
Extact Object Boundaies in Noisy Images using Level Set by: Quming Zhou Final Repot Submitted to Pofesso Bian Evans EE381K Multidimensional Digital Signal Pocessing May 10, 003 Abstact Finding object contous
More informationClustering Interval-valued Data Using an Overlapped Interval Divergence
Poc. of the 8th Austalasian Data Mining Confeence (AusDM'9) Clusteing Inteval-valued Data Using an Ovelapped Inteval Divegence Yongli Ren Yu-Hsn Liu Jia Rong Robet Dew School of Infomation Engineeing,
More informationANN Models for Coplanar Strip Line Analysis and Synthesis
200 IJCSNS Intenational Jounal of Compute Science and Netwok Secuity, VOL.8 No.10, Octobe 2008 Models fo Coplana Stip Line Analysis and J.Lakshmi Naayana D.K.Si Rama Kishna D.L.Patap Reddy Chalapathi Institute
More information3D inspection system for manufactured machine parts
3D inspection system fo manufactued machine pats D. Gacía a*, J. M. Sebastián a*, F. M. Sánchez a*, L. M. Jiménez b*, J. M. González a* a Dept. of System Engineeing and Automatic Contol. Polytechnic Univesity
More informationA Shape-preserving Affine Takagi-Sugeno Model Based on a Piecewise Constant Nonuniform Fuzzification Transform
A Shape-peseving Affine Takagi-Sugeno Model Based on a Piecewise Constant Nonunifom Fuzzification Tansfom Felipe Fenández, Julio Gutiéez, Juan Calos Cespo and Gacián Tiviño Dep. Tecnología Fotónica, Facultad
More informationMonte Carlo Simulation for the ECAT HRRT using GATE
Monte Calo Simulation fo the ECAT HRRT using GATE F. Bataille, C. Comtat, Membe, IEEE, S. Jan, and R. Tébossen Abstact The ECAT HRRT (High Resolution Reseach Tomogaph, CPS Innovations, Knoxville, TN, U.S.A.)
More informationCOMPARISON OF CHIRP SCALING AND WAVENUMBER DOMAIN ALGORITHMS FOR AIRBORNE LOW FREQUENCY SAR DATA PROCESSING
COMPARISON OF CHIRP SCALING AND WAVENUMBER DOMAIN ALGORITHMS FOR AIRBORNE LOW FREQUENCY SAR DATA PROCESSING A. Potsis a, A. Reigbe b, E. Alivisatos a, A. Moeia c,and N. Uzunoglu a a National Technical
More informationMultiview plus depth video coding with temporal prediction view synthesis
1 Multiview plus depth video coding with tempoal pediction view synthesis Andei I. Puica, Elie G. Moa, Beatice Pesquet-Popescu, Fellow, IEEE, Maco Cagnazzo, Senio Membe, IEEE and Bogdan Ionescu, Senio
More informationMethod of controlling access to intellectual switching nodes of telecommunication networks and systems
ISSN (e): 2250 3005 Volume 05 Issue 05 ay 2015 Intenational Jounal of Computational Engineeing eseach (IJCE) ethod of contolling access to intellectual switching nodes of telecommunication netwoks and
More informationTitle. Author(s)NOMURA, K.; MOROOKA, S. Issue Date Doc URL. Type. Note. File Information
Title CALCULATION FORMULA FOR A MAXIMUM BENDING MOMENT AND THE TRIANGULAR SLAB WITH CONSIDERING EFFECT OF SUPPO UNIFORM LOAD Autho(s)NOMURA, K.; MOROOKA, S. Issue Date 2013-09-11 Doc URL http://hdl.handle.net/2115/54220
More informationConfiguring RSVP-ATM QoS Interworking
Configuing RSVP-ATM QoS Intewoking Last Updated: Januay 15, 2013 This chapte descibes the tasks fo configuing the RSVP-ATM QoS Intewoking featue, which povides suppot fo Contolled Load Sevice using RSVP
More informationUsing SPEC SFS with the SNIA Emerald Program for EPA Energy Star Data Center Storage Program Vernon Miller IBM Nick Principe Dell EMC
Using SPEC SFS with the SNIA Emeald Pogam fo EPA Enegy Sta Data Cente Stoage Pogam Venon Mille IBM Nick Pincipe Dell EMC v6 Agenda Backgound on SNIA Emeald/Enegy Sta fo block Intoduce NAS/File test addition;
More informationAnnales UMCS Informatica AI 2 (2004) UMCS
Pobane z czasopisma Annales AI- Infomatica http://ai.annales.umcs.pl Annales Infomatica AI 2 (2004) 33-340 Annales Infomatica Lublin-Polonia Sectio AI http://www.annales.umcs.lublin.pl/ Embedding as a
More informationJPEG 2000 Wireless Image Transmission System using Encryption Domain Authentication
JPEG 000 Wieless Image Tansmission System using Encyption Domain Authentication Ryo Ito*, Muneaki Matsuo*, Yuya Miyaoka*, Koji Inoue**, Shoma Eguchi**, Masayuki Kuosaki*, Hioshi Ochi*, Yoshimitsu Kuoki**,
More informationRANDOM IRREGULAR BLOCK-HIERARCHICAL NETWORKS: ALGORITHMS FOR COMPUTATION OF MAIN PROPERTIES
RANDOM IRREGULAR BLOCK-HIERARCHICAL NETWORKS: ALGORITHMS FOR COMPUTATION OF MAIN PROPERTIES Svetlana Avetisyan Mikayel Samvelyan* Matun Kaapetyan Yeevan State Univesity Abstact In this pape, the class
More informationNew Algorithms for Daylight Harvesting in a Private Office
18th Intenational Confeence on Infomation Fusion Washington, DC - July 6-9, 2015 New Algoithms fo Daylight Havesting in a Pivate Office Rohit Kuma Lighting Solutions and Sevices Philips Reseach Noth Ameica
More information