Computer Vision Human Activity Recognition Using Cumulative Difference Energy Representation-Based Features and Employing Machine Learning Techniques

Author:

Sathya R.,Gokulakannan E.

Publisher

Springer Nature Singapore

Reference26 articles.

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2. Aggarwal, J., Ryoo, M., 2011. Human activity analysis: A review. ACM Comput. Surv., 0360–0300 43, 16:1–16:43. http://dx.doi.org/https://doi.org/10.1145/1922649.1922653

3. Ray, K. S. & Chakraborty, S. (2017a). An efficient approach for object detection and tracking of objects in a video with variable background, arXiv preprint [Online]. Available at: .

4. Ahad MAR, Tan JK, Kim H, Ishikawa S (2009) Temporal motion recognition and segmentation approach. Int J Imaging Syst Technol 19(2):91–99

5. Dalal N, Triggs B (2005) Histograms of oriented gradients for human detection. In: IEEE computer society conference on computer vision and pattern recognition, 2005. CVPR 2005. IEEE, vol 1, pp 886–893.

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