arXiv · 2010.13714
ActiveNet: A computer-vision based approach to determine lethargy
Abstract
The outbreak of COVID-19 has forced everyone to stay indoors, fabricating a significant drop in physical activeness. Our work is constructed upon the idea to formulate a backbone mechanism, to detect levels of activeness in real-time, using a single monocular image of a target person. The scope can be generalized under many applications, be it in an interview, online classes, security surveillance, et cetera. We propose a Computer Vision based multi-stage approach, wherein the pose of a person is first detected, encoded with a novel approach, and then assessed by a classical machine learning algorithm to determine the level of activeness. An alerting system is wrapped around the approach to provide a solution to inhibit lethargy by sending notification alerts to individuals involved.
Explore related subjects
Keep this discovery
Explore connections, maps & timelines
Aitik Gupta, Aadit Agarwal. 2020-10-26. ActiveNet: A computer-vision based approach to determine lethargy. https://doi.org/10.1145/3430984.3430986
Cite the original work for its findings. Save a collection to share your selection of sources.