Review of Pose Recognition Systems

EOI: 10.11242/viva-tech.01.04.005

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Ms.Juilee Bhombe, Mr.Aashish Jethwa, Mr.Aditya Singh, Dr. Tatwadarshi Nagarhalli, "Review of Pose Recognition Systems", VIVA-IJRI Volume 1, Issue 4, Article 5, pp. 1-8, 2021. Published by Computer Engineering Department, VIVA Institute of Technology, Virar, India.


Human motion is fundamental to understanding behaviour. In spite of advancement on single image 3 Dimensional pose and estimation of shapes, current video-based state of the art methods unsuccessful to produce precise and motion of natural sequences due to inefficiency of ground-truth 3 Dimensional motion data for training. Recognition of Human action for programmed video surveillance applications is an interesting but forbidding task especially if the videos are captured in an unpleasant lighting environment. It is a Spatial-temporal feature-based correlation filter, for concurrent observation and identification of numerous human actions in a little-light environment. Estimated the presentation of a proposed filter with immense experimentation on night-time action datasets. Tentative results demonstrate the potency of the merging schemes for vigorous action recognition in a significantly low light environment.


Action Recognition, artificial neural network, body part detection, computer vision, convolutional neural network, deep learning, deep neural network, human action recognition.


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