International Journal of Computer Science & Network Security

국제컴퓨터통신보호논문지학회 (International Journal of Computer Science & Network Security)
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Human Action Recognition Using Deep Data: A Fine-Grained Study

  • Rao, D. Surendra (Koneru Lakshmaiah Education Foundation, Guru Nanak Institutions Technical Campus) ;
  • Potturu, Sudharsana Rao (Koneru Lakshmaiah Education Foundation) ;
  • Bhagyaraju, V (Siddhartha Institute of Engineering and Technology)
  • 투고 : 2022.06.05
  • 발행 : 2022.06.30
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초록

The video-assisted human action recognition [1] field is one of the most active ones in computer vision research. Since the depth data [2] obtained by Kinect cameras has more benefits than traditional RGB data, research on human action detection has recently increased because of the Kinect camera. We conducted a systematic study of strategies for recognizing human activity based on deep data in this article. All methods are grouped into deep map tactics and skeleton tactics. A comparison of some of the more traditional strategies is also covered. We then examined the specifics of different depth behavior databases and provided a straightforward distinction between them. We address the advantages and disadvantages of depth and skeleton-based techniques in this discussion.

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참고문헌

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