A method for real-time implementation of HOG feature extraction

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1 Invted Paper A method for real-tme mplementaton of HO feature etracton LUO Ha-bo 134 YU Xn-rong 1345 LIU Hong-me 5 DIN Qng-ha 6 1. Shenang Insttute of Automaton Chnese Academ of Scences Shenang PR Chna;. raduate School Chnese Academ of Scences Beng PR Chna 3. Ke Laborator of Optcal-Electroncs Informaton Processng Chnese Academ of Scence Shenang PR Chna; 4. Ke Laborator of Image Understandng and Computer Vson Laonng Provnce PR Chna; 5. AVIC HONDU Avaton Industr roup LTD ; Nanchang 33004; PR Chna; 6. Research Insttute of eneral Development and Demonstraton of Equpment Equpment of Ar Force Beng Chna Abstract Hstogram of orented gradent HO s an effcent feature etracton scheme and HO descrptors are feature descrptors whch s wdel used n computer vson and mage processng for the purpose of bometrcs target trackng automatc target detectonatd and automatc target recogntonatr etc. However computaton of HO feature etracton s unsutable for hardware mplementaton snce t ncludes complcated operatons. In ths paper the optmal desgn method and theor frame for real-tme HO feature etracton based on FPA were proposed. The man prncple s as follows: frstl the parallel gradent computng unt crcut based on parallel ppelne structure was desgned. Secondl the calculaton of arctangent and square root operaton was smplfed. Fnall a hstogram generator based on parallel ppelne structure was desgned to calculate the hstogram of each sub-regon. Epermental results showed that the HO etracton can be mplemented n a pel perod b these computng unts. Ke words: hstogram of orented gradent HO feature etracton real-tme mplementaton parallel ppelne 1 INTRODUCTION HO descrptors are feature descrptors used n computer vson and mage processng to detect obect. Ths technque counts occurrences of gradent orentaton n localzed portons of an mage. Ths method s smlar to that of edge orentaton hstograms scale-nvarant feature transform descrptors and shape contets [1]. Dalal and Trggs [] ponted out that HO descrptors sgnfcantl outperform estng feature sets for human detecton after studng the queston of feature sets for robust vsual obect recognton. Wang and uan [3] presented a novel method to mplement graph cut for vdeo obect segmentaton the combned HO feature to ncorporate a shape pror nto graph cut algorthm as a new wa to enhance vdeo obect segmentaton accurac. In lterature [4] HO descrptors were adopted to perform onlne classfcaton durng obect trackng process. However computaton of HO feature etracton s too comple for real-tme mplementaton and due to the ncreasng of crcut sze caused b straghtforward hardware mplementaton of HO feature etracton t s unsutable for hardware mplementaton so t s ndspensable to smplf and modf the computaton scheme n order to acheve effcent mplementaton sutable for real-tme sstems. In lterature [5] several methods to smplf the computaton of Internatonal Smposum on Photoelectronc Detecton and Imagng 011: Advances n Infrared Imagng and Applcatons Jeffer J. Puschell Junhao Chu Hame ong Jn Lu Eds. Proc. of SPIE Vol SPIE CCC code: X/11/$18 do: / Proc. of SPIE Vol Downloaded from SPIE Dgtal Lbrar on 03 Ma 01 to Terms of Use:

2 HO feature etracton was proposed but so much specfc smplfcaton was appled and resulted n a bad nfluence on calculaton accurac. Furthermore computaton magntude of gradent b usng a look-up-table consumes too much memor resource. In ths paper we proposed a new method for real-tme mplementaton of HO feature etracton. The method can acheve hgher precson n calculaton wth less logc and memor cost and s more sutable for real-tme HO feature etracton. HISTORAMS OF ORIENTED RADIENTS [5] The essental dea behnd the Hstogram of Orented radent descrptors s that local obect appearance and shape wthn an mage can be descrbed b the dstrbuton of ntenst gradents or edge drectons. The mplementaton of these descrptors can be acheved b dvdng the mage nto small connected regons called cells and for each cell complng a hstogram of gradent drectons or edge orentatons for the pels wthn the cell. The combnaton of these hstograms then represents the descrptor. For mproved accurac the local hstograms can be contrast-normalzed b calculatng a measure of the ntenst across a larger regon of the mage called a block and then usng ths value to normalze all cells wthn the block. Based on the above eplanaton HO feature etracton conssts of man hstograms of orentated gradents n localzed areas of an mage. In ths eplanaton computaton of HO feature etracton s dvded nto the followng three steps..1 radent computaton In HO feature etracton frst of all 1st order dfferental coeffcents and are computed b the followng equatons. where f means lumnance at. f + 1 f f + 1 f Then magntude m and drectonθ of the computed gradents are computed b the followng epressons respectvel. m + arctan θ 3. Hstogram generaton After obtanng the values of m andθ hstograms are generated as follows: 1 Determne the class whch θ belongs to Increase the value of the class determned b step 1 3 Repeat above operatons for all gradents belong to the cell. In order to reduce the effect of alasng the values of two neghborng classes are ncreased. The ncrement make n ndcates a class number whch θ belongs to and n+1 would be the class whch s the nearest one to class n. The ncreased values m n and m n+1 are computed as follows: 1 Proc. of SPIE Vol Downloaded from SPIE Dgtal Lbrar on 03 Ma 01 to Terms of Use:

3 + 1 1 m m m m b n n n α α π θ 4 Where b ndcates the total number of classes α s a parameter for proportonal dstrbuton of magntude m whch s defned as the dstance from θ to class n and n+1 b b π θ π α mod 5.3 Hstogram normalzaton Fnall a large hstogram s created b combnng all generated hstograms belongng to a block conssts of some cells. In order to reduce the nfluence of varatons n llumnaton and contrast L1-norm s adopted n ths paper. After obtanng the large combned hstogram t can be normalzed as follows: + ε k k V V v 6 where V k s the vector correspondng to a combned hstogram for the block ε s a small constant and v s the normalzed vector whch s a fnal HO feature. 3 REAL-TIME IMPLEMENTATION OF HO FEATURE EXTRACTION In ths secton how to reduce computatonal complet of HO feature etracton and how to evaluate the calculaton accurac wth the proposed smplfcaton wll be descrbed. Based on ths dscusson a method for real-tme mplementaton of HO feature etracton s proposed. 3.1 Computaton of gradent Computaton of gradent s the second step of HO etracton and has square root and arctangent operatons descrbed as equaton and equaton 3 respectvel. Accordng to equaton straghtforward hardware mplementaton of gradent magntude computaton costs too much logc resources or memor and s hardl realzed n hardware-based real-tme sstems. Dealng wth equaton t can be reformed nto the followng equatons: < + > + / 1 / 1 m m m 7 Then the square root operaton s transformed nto 1 + wth 0 1. It can be appromated wth mult-lnear functon. Thus n our mplementaton the square root operaton s mplemented b usng a 16 elements reduced look-up-table and lnear computaton accordng to equaton 8. The curve n Fgure 1 shows the error of the proposed Proc. of SPIE Vol Downloaded from SPIE Dgtal Lbrar on 03 Ma 01 to Terms of Use:

4 algorthm n calculaton of 1+ and the largest error s k LUTk + 1 LUTk 8 1+ k /16 where LUT k and LUT k+1 ndcate the kth and k+1th elements of look-up-table respectvel Error Fgure 1. Error curve of the proposed algorthm n calculaton of 1 + For the arctangent operaton two solutons can be adopted. One s drectl usng a look-up-table of arctan whle the other s computng t wth a Talor epanson as equaton 9. However the frst one costs plent of memor and the second one converges onl n the nterval of [-1 1]. Moreover the convergent rate decreases rapdl wth the ncreasng of. For eample when tems n equaton 9 must be calculated to lmt the calculaton error to 0.1. These calculatons wll consume large amount of multplng unts. Therefore drectl calculatng arctan wth equaton 9 n ts whole defnton doman s not preferable. arctan k k 9 k 1 k Snce arctangent s an odd functon arctan n [- + ] can be obtaned b ts values n [0 + ] thus equaton 3 can be reformed nto the followng equatons: θ arctan θ 0.5π / arctan / > Hence the computaton of arctan n [0 + ] doman was transformed nto [0 1]. Moreover when >0.5 supposeθ arctan arctan0.5 + α and tan α arctan can be deduced b the followng equatons: 10 + θ arctan arctan0.5 + arctan 11 Proc. of SPIE Vol Downloaded from SPIE Dgtal Lbrar on 03 Ma 01 to Terms of Use:

5 Furthermore when 0.5 < θ arctan arctan0.5 + arctan. 1 In addton arctan n [0 0.5] can be smplfed as the lnear functon n 1 f the requred precson s not so strct: arctan0.5 arctan Fnall n our mplementaton arctangent operaton can be obtaned b ontl usng equaton and 13. The curve n Fgure shows the error of the proposed algorthm n calculaton of arctan and the largest error s Errordegree Fgure. Error curve of the proposed algorthm n calculaton of arctan 3. Hstogram generaton In ths step class value s ncreased usng magntude m and θ accordng to equaton 4 and 5. In order to ncrease throughput effcentl the hstogram generator adopts ppelne archtecture as shown n Fgure 3. In our mplementaton the number of classes s 9 so the hstogram storage s composed wth 9 blocks embedded dual port RAM. In ths paper m n s accessed through ther rght port named Rp and m n+1 s accessed through ther left port named Lp. D q CCflWut1JTO Fgure 3. Hstogram generator archtecture Proc. of SPIE Vol Downloaded from SPIE Dgtal Lbrar on 03 Ma 01 to Terms of Use:

6 A4!CJ 3.3 Hardware archtecture for hog feature etractor Based on the above dscusson we propose hardware archtecture sutable for real-tme HO feature etracton whch s descrbed n Fgure 4. Wth ths archtecture computaton of HO feature etracton s performed as follows: 1 Images are nput to the shft regster lne b lne radent calculator receves the nput mages for computng magntude and drecton of gradents 3 Hstograms are generated usng computed magntude and drecton of gradents meanwhle the sum of gradent magntude n each cell s calculatedl1-norm 4 Fnall the hstograms are normalzed and output H0L!0U1 LCLJ DCOL ToLa a1olj CJCut1JTOL bbu ccnwn10 4OLW1J Fgure 4. Hardware archtecture for proposed HO feature etractor 4 EVALUATION In order to evaluate the proposed archtecture t s mplemented on an ALTERA Cclone III FPA. Detals are shown n Table 1 and the mplementaton results are shown n Table. B ths mplementaton onl one ccle s requred to compute HO feature etracton for each pel wth 3 ccles dela. Table 1: Parameters Input mage pels Cell 8 8 pels Block 4 4 cells Step strde 8 pels vertcall and horzontall The number of classes 9 Table : Implementaton results Faml Cclone III Devce EP3C5F56C6 Total logc elements 937/513618% Total combnatonal functons 880/513617% Dedcated logc regsters 175/51363% Total regsters 175 Total memor bts / % Embedded Multpler 9-bt elements 3/467% Total PLLs 1/50% Proc. of SPIE Vol Downloaded from SPIE Dgtal Lbrar on 03 Ma 01 to Terms of Use:

7 5 CONCLUSION In ths paper a method for real-tme mplementaton of HO feature etracton was proposed. To reduce computatonal complet and make effcent hardware archtecture ths paper descrbes how to smplf the computaton of HO feature etracton ncludng the computaton of arctangent operaton gradent magntude and hstogram generaton. To evaluate crcut sze and processng performance the proposed method was mplemented on a sngle ALTERA Cclone III FPA chp. As a result onl one ccle s requred to compute HO feature etracton for each pel wth 3 ccles dela. The epermental results show that the proposed method s further sutable for real-tme HO feature etracton. Moreover the proposed method for arctangent computaton and gradent magntude computaton can be used n the sstem whch contans gradent computaton such as SIFT phase congruenc feature etracton and so on. REFERENCES [1] Hstogram of orented gradents. [] Dalal N. Trggs B.. Hstograms of orented gradents for human detecton Proceedngs of the 005 IEEE Computer Socet Conference on Computer Vson and Pattern Recognton CVPR 05 pp [3] Wang Chun-haoLng uan Lng. raph Cut Vdeo Obect Segmentaton usng Hstogram of Orented radents Proceedngs of the 008 IEEE Internatonal Smposum on Crcuts and Sstems ISCAS 008 pp [4] Xao Jangan Cheng Hu and Feng Han etc. Obect Trackng and Classfcaton n Aeral Vdeos Proceedngs of the 009 SPIE Automatc Target Recognton XVIII Vol pp [5] Kadota Ro Sugano Hrok and Hromoto Masauk etc. Hardware Archtecture for HO Feature Etracton Proceedngs of the 009 IEEE Intellgent Informaton Hdng and Multmeda Sgnal Processng pp LUO Ha-bo E-mal: luohb@sa.cn Proc. of SPIE Vol Downloaded from SPIE Dgtal Lbrar on 03 Ma 01 to Terms of Use: