References

Bodla, N., B. Singh, R. Chellappa and L.S. Davis, 2017. Soft-NMS-improving object detection with one line of code. Proceedings of the IEEE International Conference on Computer Vision, October 22-29, 2017, IEEE, Venice, Italy, pp: 5561-5569.

Dalal, N. and B. Triggs, 2005. Histograms of oriented gradients for human detection. IEEE Comput. Soc. Conf. Comput. Vision Pattern Recognition, 1: 886-893.
CrossRef  |  Direct Link  |  

Papageorgiou, C.P., M. Oren and T. Poggio, 1998. A general framework for object detection. Proceedings of the 6th International Conference on Computer Vision (IEEE Cat. No. 98CH36271), January 7, 1998, IEEE, Bombay, India, pp: 555-562.

Singh, S. and R. Mittal, 2015. Image segmentation using edge detection and poincare mapping method. Eur. J. Adv. Eng. Technol., 2: 81-83.

Taleb, N.O., A. Chergui, M.L.B. Maati and M.F. Nanne, 2016. Overview on automatic detection of human body. Proceedings of the 2016 5th International Conference on Multimedia Computing and Systems (ICMCS), September 29-October 1, 2016, IEEE, Marrakech, Morocco, pp: 671-675.

Viola, P. and M. Jones, 2001. Rapid object detection using a boosted cascade of simple feature. IEEE Conf. Comput. Vision Pattern Recogn., 1: 511-518.
Direct Link  |  

Viola, P. and M.J. Jones, 2004. Robust real-time face detection. Int. J. Comput. Vision, 57: 137-154.
CrossRef  |  

Viola, P., M.J. Jones and D. Snow, 2005. Detecting pedestrians using patterns of motion and appearance. Int. J. Comput. Vision, 63: 153-161.
CrossRef  |  

Viola, P., M.J. Jones and D. Snow, 2005. Detecting pedestrians using patterns of motion and appearance. Int. J. Comput. Vision, 63: 153-161.
CrossRef  |  

Wang, M.S. and Z.R. Zhang, 2018. FPGA implementation of HOG based multi-scale pedestrian detection. Proceedings of the 2018 IEEE International Conference on Applied System Invention (ICASI), April 13-17, 2018, IEEE, Chiba, Japan, pp: 1099-1102.

Wu, B. and R. Nevatia, 2006. Tracking of multiple, partially occluded humans based on static body part detection. Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR’06), June 17-22, 2006, IEEE, New York, USA., pp: 951-958.

Wu, B. and R. Nevatia, 2007. Detection and tracking of multiple, partially occluded humans by bayesian combination of edgelet based part detectors. Int. J. Comput. Vision, 75: 247-266.
CrossRef  |  Direct Link  |  

Zhang, S., R. Benenson and B. Schiele, 2015. Filtered feature channels for pedestrian detection. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, June 7-12, 2015, IEEE, Boston, Massachusetts, pp: 1751-1760.

Zhang, S., R. Benenson, M. Omran, J. Hosang and B. Schiele, 2016. How far are we from solving pedestrian detection?. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, June 27-30, 2016, IEEE, Las Vegas, Nevada, pp: 1259-1267.

Zhang, X., L. Cheng, B. Li and H.M. Hu, 2018. Too far to see? Not really!-Pedestrian detection with scale-aware localization policy. IEEE. Trans. Image Process., 27: 3703-3715.
CrossRef  |  Direct Link  |  

Zhao, J., J. Li and Y. Ma, 2018. RPN+ fast boosted tree: Combining deep neural network with traditional classifier for pedestrian detection. Proceedings of the 2018 4th International Conference on Computer and Technology Applications (ICCTA), May 3-5, 2018, IEEE, Istanbul, Turkey, pp: 141-150.

Zhu, Q., M.C. Yeh, K.T. Cheng and S. Avidan, 2006. Fast human detection using a cascade of histograms of oriented gradients. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Volume 2, June 17-22, 2006, New York, USA., pp: 1491-1498.

Zhu, Q., M.C. Yeh, K.T. Cheng and S. Avidan, 2006. Fast human detection using a cascade of histograms of oriented gradients. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Volume 2, June 17-22, 2006, New York, USA., pp: 1491-1498.