LogRegression: human action pattern recognition for yoga and kavayat for children

Abstract

Poses of human pattern recognition through machine learning is an essential facet of several applications, including health, surveillance, and sports analysis. For children yoga and kavayat (mock drill) increases the physical as well as mental health. Through the analysis of motion data this work discriminates between varied actions with high precision, contribution valued insights for monitoring and analysis in real-time. Here, this system that influences technique called as machine learning specifically logistic regression, to precisely discriminate and classify physical action patterns (child pose estimation) of children. Analogous to the propagation of false information, identifying physical actions is essential for upholding integrity and efficiency across various domains. The novel system demonstrates a towering accuracy of 98.00%, highlighting its effectiveness in recognizing and classifying physical action patterns.