An Approach using Multiple features to detect Multi-view Human Activity

  • Ankur Chaturvedi

Abstract

Dynamic nature of human activities is the cause of various factors that had been thetarget of research field to put it into decodable framework. This paper targets at Multifaceted interpretation of human image at a given instance through model. The Paperproposes to approach the given problem with the help of Hidden Markov Model(HMMs) which would proceed first by detecting and locating a specific logical imageand then interpreting its logical arguments behind it. The approach involves threedistinct concepts such as optical flow to detect motion feature, contour to detectdistance signal feature and LBP which is rotational invariant. Our proposed work wastested successfully in our own dataset. With the help of experimental result over thedataset, it is found that the our framework is efficient and flexible to detect multihuman activity.

Published
2020-06-06
How to Cite
Ankur Chaturvedi. (2020). An Approach using Multiple features to detect Multi-view Human Activity. International Journal of Advanced Science and Technology, 29(04), 6612 - 6617. Retrieved from http://sersc.org/journals/index.php/IJAST/article/view/27996