Human Activity Recognition using SVM and Deep Learning
European Journal of Molecular & Clinical Medicine,
2020, Volume 7, Issue 4, Pages 1984-1990
AbstractHuman activity recognition is one among the foremost vital rising technology. Principle parts from the body parts territory are utilized for human movement acknowledgment to scale back spatial property. A multi scale delineation human action acknowledgment is done to save the segregate data before spatial property decrease. This paper could be a human action Recognition system for identification of person. It takes input a video of COVID-19 patients and searches for a match within the hold on pictures. This method is predicate d on Gabor options extraction mistreatment Gabor filter. For feature extraction the input image is matching with Gabor filter and further personal sample generation formula is employed to pick out a collection of informative and non redundant Gabor options. DNN (Deep learning Models) is used for matching the input human action image to the hold on pictures. This method is used in hospital management application for detecting the COVID-19 patient activity from surveillance cameras. By using the SVM and deep learning the human activity is recognized using matlab tool.
- Article View: 59
- PDF Download: 108