Automatic human posture estimation for sport activity recognition with robust body parts detection and entropy markov model

• Published in: Multimedia tools and applications Vol. 80; no. 14; pp. 21465 - 21498
• Main Authors: Nadeem, Amir, Jalal, Ahmad, Kim, Kibum
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.06.2021; Springer Nature B.V
• Subjects: Activity recognition; Body parts; Computer Communication Networks; Computer Science; Data Structures and Information Theory; Discriminant analysis; Emission analysis; Entropy; Fitness; Markov chains; Maximum entropy; Multimedia Information Systems; Optical flow (image analysis); Robustness; Sensors; Service robots; Special Purpose and Application-Based Systems; Statistical analysis; Statistical methods; Virtual reality; Entropy Markov model; Multidimensional cues; Body parts detection; Sports activity recognition; Posture estimation

Automated human posture estimation (A-HPE) systems need delicate methods for detecting body parts and selecting cues based on marker-less sensors to effectively recognize complex activity motions. Recognition of human activities using vision sensors is a challenging issue due to variations in illumi...