Acknowledgement
Grant : 사물인터넷 기반 영상보안용 초저전력 SoC 핵심 IP 기술 개발
References
- J. Hsiehm, S. Yu, Y. Chen, and W. Hu, “Automatic traffic surveillance system for vehicle tracking and classification,” IEEE transactions on Intelligent Transportation Systems, vol. 7, no 2, pp. 175-187, 2006. https://doi.org/10.1109/TITS.2006.874722
- J. Black, S. Velastin, and B. Boghossian, “A real time surveillance system for metropolitan railways,” IEEE Conf. on Advanced Video and Signal Based Surveillance, pp. 189-194, Sep. 2005.
- C. Stauffer, and W. Grimson, “Adaptive background mixture models for real-time tracking,” Proc. Computer Vision and Pattern Recognition, vol. 2, pp. 246-252, Jun. 1999.
- D. Lee, “Effective Gaussian Mixture Learning for Video Background Subtraction,” IEEE Transaction on Pattern Analysis and Machine Intelligence, vol. 27, no. 5, pp. 827-832, May 2005. https://doi.org/10.1109/TPAMI.2005.102
- S. Kulchandani, and J. Dangarwala, “Moving object detection: Review of recent research trends,” Pervasive Computing (ICPC), 2015 International Conference, Jan. 2015.
- M. Piccardi, “Background subtraction techniques: A review,” Proc. IEEE Int. Conf. Syst., Man Cybern., vol. 4, pp. 3099-3104, Oct. 2004.
- K. Kim, T. Chalidabhongse, D. Harwood, and L. Davis, “Real-time foreground-background segmentation using code-book model,” Real-Time Imag., Special Issue on Video Object Processing, vol. 11, pp. 172-185, Jun. 2005.
- A. Elgammal, R. Duraiswami, D. Harwood, and L.S. Davis, “Background and foreground modeling using nonparametric kernel density estimation for visual surveillance,” Proc. IEEE, vol. 90, no. 7, pp. 1151-1163, Jul. 2002. https://doi.org/10.1109/JPROC.2002.801448
- Xia Dong, Kedian Wang, and Guohua Jia, “Moving Object and Shadow Detection Based on RGB Color Space and Edge Ratio,” IEEE 2nd International Conf. on Image and Signal Processing, pp. 1 -5, Oct. 2009.
- Jin Min Choi, Hyung Jin Chang, Yung Jun Yoo, and Jin Young Choi, “Robust moving object detection against fast illumiation change,” Computer Vision and Image Understanding, pp. 179-193, 2012. https://doi.org/10.1016/j.cviu.2011.10.007
- Jinhai Xiang, Heng Fan, Honghong Liao, Jun Xu, Weiping Sun, and Shengsheng Yu, “Moving object detection and Shadow Removing under Changing Illumination Condition,” Mathematical Problems in Engineering, pp. 1-10, Feb. 2014.
- P. Suo, and Y. Wang, “An improved adaptive background modeling algorithm based on Gaussian Mixture Model,” ICSP 2008. 9th International Conference on, Oct. 2008.
- P.-L. St-Charles, G.-A. Bilodeau, and R. Bergevin, “A Self-Adjusting Approach to Change Detection Based on Background Word Consensus,” IEEE Winter Conference on Applications of Computer Vision (WACV), Jan. 6-9, 2015.
- M. Hofmann, P. Tiefenbacher, and G. Rigoll, “Background Segmentation with Feedback: The Pixel-Based Adaptive Segmenter,” Proc. of IEEE Workshop on Change Detection, June, 2012.
- M. Van Droogenbroeck, and O. Paquot, “Background Subtraction: Experiments and Improvements for ViBe,” Proc of IEEE Workshop on Change Detection, CVPR, June, 2012
- J. S Lim, “Hardware Implementation of Background Subtraction Algorithm,” Graduate School, Kyungbuk University, Dec. 2006.