Implementation of Omni-directional Image Viewer Program for Effective Monitoring

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2 : (So-Yeon Jeon et al.: Implementation of Omni-directional Image Viewer Program for Effective Monitoring) (Regular Paper) 23 6, 2018 11 (JBE Vol. 23, No. 6, November 2018) https://doi.org/10.5909/jbe.2018.23.6.939 ISSN 2287-9137 (Online) ISSN 1226-7953 (Print) a), b), b) Implementation of Omni-directional Image Viewer Program for Effective Monitoring So-Yeon Jeon a), Cheong-Hwa Kim b), and Goo-Man Park b). Normal mode, ROI(Region of Interest) mode, Tracking mode, Auto-rotation mode,. Normal mode,,, ROI mode. Auto-rotation mode, Tracking mode,.,. Abstract In this paper, we implement a viewer program that can monitor effectively using omni-directional images. The program consists of four modes: Normal mode, ROI(Region of Interest) mode, Tracking mode, and Auto-rotation mode, and the results for each mode is displayed simultaneously. In the normal mode, the wide angle image is rendered as a spherical image to enable pan, tilt, and zoom. In ROI mode, the area is displayed expanded by selecting an area. And, in Auto-rotation mode, it is possible to track the object by mapping the position of the object with the rotation angle of the spherical image to prevent the object from deviating from the spherical image in Tracking mode. Parallel programming for processing of multiple modes is performed to improve the processing speed. This has the advantage that various angles can be seen compared with surveillance system having a limited angle of view. Keyword : Video analysis system, Spherical image mapping, Object tracking, Auto-rotation a) IT(Dept. of Media IT Engineering, The Graduate School, Seoul National Univ. of Science & Technology) b) IT(Dept. of Electronic & IT Media Engineering, Seoul National Univ. of Science & Technology) Corresponding Author : (Gooman Park) E-mail: gmpark@seoultech.ac.kr Tel: +82-2-970-6430 ORCID: https://orcid.org/0000-0002-7055-5568 This research was supported by the Commercializations Promotion Agency for R&D Outcomes(COMPA) funded by the Ministry of Science and ICT(MSIT).[2018K000030, Development of Spherical Rendering Display and Intelligent video analytic algorithm using Real-Time IP Camera] Manuscript received October 16, 2018; Revised November 19, 2018; Accepted November 19, 2018. Copyright 2016 Korean Institute of Broadcast and Media Engineers. All rights reserved. This is an Open-Access article distributed under the terms of the Creative Commons BY-NC-ND (http://creativecommons.org/licenses/by-nc-nd/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited and not altered.

(JBE Vol. 23, No. 6, November 2018). CCTV(Closed Circuit Television), PTZ(Pan-Tilt-Zoom). PTZ pan, tilt, zoom CCTV [1]. PTZ FOV(Field of View),. 360,. PTZ PTZ. 2, 3, 4... /. 1. Fig. 1. Configuration of Proposed Program 2. : 180 Fig. 2. Input Image : Two Images of 180 degrees

2 : (So-Yeon Jeon et al.: Implementation of Omni-directional Image Viewer Program for Effective Monitoring).,. Normal mode, ROI(Region of Interest) mode, Tracking mode, Auto-rotation mode. 180, 2. 1. Normal Mode Normal mode equirectangular, [2,3,4].,, / [5]. z, / x, y,,.. 1, x, y,. 2, width, height.,,. 0.1. 2. ROI Mode ROI mode Normal mode. Normal mode 1., / Table 1. Pseudo Code of Mouse Event for Rotation, Zoom In/Out Rotation _ _ Zoom In/Out if if 3., / Fig. 3. The Result of Rotation, Zoom In/Out in Spherical Image

(JBE Vol. 23, No. 6, November 2018),. 4 ROI mode. 4. ROI Mode Fig. 4. The Process of ROI Mode 3. Tracking Mode, [6,7,8]., equirectangular. bounding box,. 4. Auto-Rotation Mode,.. [9]. Auto-rotation mode x, y.,. PTZ CCTV,. equirectangular x, y, x, y. 6. x, y x, y., x [0, 360], y [0, 180]. x, y [0, 360], [0, 180].. 5. Tracking Mode Fig. 5. The Process of Tracking Mode

2 : (So-Yeon Jeon et al.: Implementation of Omni-directional Image Viewer Program for Effective Monitoring) 6. Fig. 6. Conversion from Coordinates in Rectangular Image to Rotation Angles in Spherical Image 7. Auto-rotation Mode Fig. 7. The Process of Auto-rotation Mode (1),,,,,,., Auto-rotation mode.. 8,., IP(Internet Protocol),,. UI. Normal mode, on/off., Full mode., 8. Fig. 8. Configuration of Initial Dialog

(JBE Vol. 23, No. 6, November 2018) 180.,. 9, 11 ( 10). (Normal mode), Normal mode, ROI mode, Tracking mode, Auto-rotation mode. Full mode,. ROI mode Tracking mode, Auto-rotation mode Tracking mode. 9. Fig. 9. Configuration of Main Dialog 10. Fig. 10. Input Image for Program

2 : (So-Yeon Jeon et al.: Implementation of Omni-directional Image Viewer Program for Effective Monitoring) 11. Fig. 11. Result of Program Implementation,. GPU(Graphic Processing Unit) CUDA(Compute Unified Device Architecture), CUDA 9.0, cudnn 5.1. Equirectangular, [10,11]. 2. Table 2. Speed by Operation Processing Method Processing Method Image Size(pixel) ( 단위 : fps) CPU TBB GPU 380 380 2 4 20 90 760 760 2 0.9 1.2 44 2. 360 360, 760 760 Euirectangu- lar, CPU, TBB(Threading Building Blocks) CUDA GPU...,.,. CCTV [12]..,.

(JBE Vol. 23, No. 6, November 2018) (References) [1] Y.K. Kim, G.M. Um, K.S. Cho, Object-of-Interest Oriented Multi-Angle Video Acquisition Technique Using Object-Tracking based on Multi-PTZ Camera Position Control, Electronics and Telecommunications Trends, Vol.31, No. 3, pp.1-8, 2016. [2] Bosung Kim, JonSeung Park, "Exemplar-Based Image Inpainting for Spherical Panoramic Image", Journal of Korean Institute of Information Scientists and Engineers, Vol. 43, No.4, pp. 437-449, 2016. [3] Gyeong-il Kweon, Young-ho Choi, "Image-processing Based Panoramic Camera Employing Single Fisheye Lens", Journal of the Optical Society of Korea, Vol. 14, No. 3, pp.245-259, 2010 [4] Shigang Li, Member, IEEE, "Monitoring Around a Vehicle by a spherical Image Sensor", IEEE Transactions on Intelligent Transportation Systems, Vol. 7, No. 4, pp.541-550, 2006. [5] Gooman Park, Jihye Jeon, Jihee Yang, Jiwoong Jang, The Method of 360 Degrees Spherical Rendering Display and Auto Video Analytic Using Real-time Image Acquisition Cameras, 10-1639275, Korea, 2016. [6] Jun-Hwan Lee and Jisang Yoo, "Real-time Face Tracking Method using Improved Camshift", JBE Vol. 21, No. 6, pp.861-877, 2016. [7] Ming TANG and Jiayi FENG, Multi-kernel Correlation Filter for Visual Tracking, IEEE International Conference on Computer Vision, 2015. [8] Joao F. Henriques, Rui Caseiro, Pedro Martins, and Jorge Batista, "High-Speed Tracking with Kernelized Correlation Filters", IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol,37, No 3, pp.583-596, 2015, doi: 10.1109/TPAMI.2014.2345390 [9] Ivan Markovic, François Chaumette, Ivan Petrovic. Moving object detection, tracking and following using an omnidirectional camera on a mobile robot, IEEE Int. Conf. on Robotics and Automation, ICRA 14, Jun 2014, Hong-Kong, Hong Kong SAR China. 2014. <hal- 00949336> [10] Seoung Heon Kang, Seoung-Jae Lee, Man Hee Lee and In Kyu Park, "Parallelization of Feature Detection and Panorama Image Generation using OpenCL and Embedded GPU", JBE Vol.19, No. 3, pp.316-328, 2014. [11] Dongmin Park, Dongkyu Lee and SeoungJun Oh, "Introduction to GPU Computing and CUDA Programming: A Case Study on FDTD", IEEE Antennas and Propagation Magazine, Vol. 52, No. 3, 2010, 06. [12] Paul Bourke, Converting an Equirectangular Image to a Perspective Projection, 2016, 10. - 2017 : IT - 2017 ~ : IT - ORCID : https://orcid.org/0000-0003-3026-6662 - :, - 2016 ~ : IT - ORCID : https://orcid.org/0000-0002-8947-8371 - :, - 1984 : - 1986 : - 1991 : - 1991 ~ 1996 : - 1996 ~ 1999 : - 1999 ~ : IT( TI ) - 2006 ~ 2007 : Georgia Institute of Technology Dept.of Electrical and Computer Engineering, Visiting Scholar - ORCID : https://orcid.org/0000-0002-7055-5568 - :,