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Abstract
I. INTRODUCTION
II. RELATED WORK
III. DATASET FOR RECOGNITION OF HUMAN ACTIONS
IV. DESIGN AND METHODOLOGY
V. RESULTS AND DISCUSSION
VI. CONCLUSION
REFERENCES
Y. Chen, W. Ke, K. H. Chan, and Z. Xiong, “A human activity recognition approach based on skeleton extraction and image reconstruction,” in Proceedings of 2021 the 5th International Conference on Graphics and Signal Processing, Nagoya, Japan, 2021, pp. 1-8.
A. Rao, “Efficient min-cost real time action recognition using pose estimates,” in Proceedings of 2020 IEEE International Conference for Innovation in Technology (INOCON), Bangluru, India, 2020, pp. 1-6.
Z. Cao, T. Simon, S. E. Wei, and Y. Sheikh, “Realtime multiperson 2D pose estimation using part affinity fields,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Honolulu, HI, 2017, pp. 1302-1310.
A. Singh, D. Patil, and S. N. Omkar, “Eye in the sky: real-time drone surveillance system (DSS) for violent individuals identification using ScatterNet hybrid deep learning network,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, Salt Lake City, UT, 2018, pp. 1629-1637.
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