Depth and Thermal Image Fusion for Human Detection with Occlusion Handling Under Poor Illumination from Mobile Robot

Author:

Hasim Saipol Hadi,Mamat Rosbi,Sheikh Usman Ullah,Amin Shamsuddin Hj. Mohd.

Publisher

Springer International Publishing

Reference34 articles.

1. Xia, L., Chen, C., Aggarwal, J.K.: Human detection using depth information by kinect. In: Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2011 IEEE, pp. 15–22 (2011)

2. Eng, H., Wang, J., Kam, A.H., Yau, W.A.: Bayesian framework for robust human detection and occlusion handling using human shape model. In: Proceedings of the 17th International Conference on ICPR 2004, vol. 2, pp. 257–260 (2004)

3. Kamijo, S., Matsushita, Y., Ikeuchi, K., Sakauchi, M.: Occlusion robust tracking utilizing spatio-temporal Markov random field model. In: Proceedings of 15th International Conference on Pattern Recognition ICPR-2000 [Internet], vol. 1, pp. 140–144. IEEE Computer Society (200). http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=905292

4. Otsuka, K., Mukawa, N.: Multiview occlusion analysis for tracking densely populated objects based on 2-D visual angles. In: Proceedings of 2004 IEEE Computer Society Conference on Computer Vision Pattern Recognition, 2004 CVPR 2004 [Internet], vol. 1, pp. 90–97. IEEE (2004). http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=1315018

5. Ikemura, S., Fujiyoshi, H.: Real-time human detection using relational depth similarity features. Computer Vision—ACCV 2010. Lecture Notes in Computer Science, vol. 6495, pp. 25–38 (2011)

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