Paper Info
Title
Automatic Human Posture Estimation For Sport Activity Recognition With Robust Body Parts Detection And Entropy Markov Model
Abstract
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 illumination conditions and complex movements during the monitoring of sports and fitness exercises. In this paper, we propose a novel A-HPE method that intelligently identifies human behaviours by utilizing saliency silhouette detection, robust body parts model and multidimensional cues from full-body silhouettes followed by an entropy Markov model. Initially, images are pre-processed and noise is removed to obtain a robust silhouette. Body parts models are then used to extract twelve key body parts. These key body parts are further optimized to assist the generation of multidimensional cues. These cues include energy, optical flow and distinctive values that are fed into quadratic discriminant analysis to discriminate cues which help in the recognition of actions. Finally, these optimized patterns are further processed by a maximum entropy Markov model as a recognizer engine based on transition and emission probability values for activity recognition. For evaluation, we used a leave-one-out cross validation scheme and the results outperformed existing well-known statistical state-of-the-art methods by achieving better body parts detection and higher recognition accuracy over four benchmark datasets. The proposed method will be useful for man-machine interactions such as 3D interactive games, virtual reality, service robots, e-health fitness, and security surveillance.
Year
DOI
Venue
2021
10.1007/s11042-021-10687-5
MULTIMEDIA TOOLS AND APPLICATIONS
Keywords
DocType
Volume
Body parts detection, Entropy Markov model, Multidimensional cues, Sports activity recognition, Posture estimation
Journal
80
Issue
ISSN
Citations 
14
1380-7501
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Amir Nadeem100.34
Ahmad Jalal215311.00
Kibum Kim313618.81