Combining Template Matching and Model Fitting for Human Body Segmentation and Tracking with Applications to Sports Training

摘要

This paper present a method for extracting and automatic tracking of human body using template matching and human body model fitting for specific activity. The method includes training and testing stages. For training, the body shapes are manually segmented from image sequences as templates and are clustered. The 2D joint locations of each cluster center are labeled and the dynamical models of the templates are learned. For testing, a "seed" frame is first selected from the sequence according to the reliability of motion segmentation and several most matched templates to it are obtained. Then, a template tracking process within a probabilistic framework integrating the learnt dynamical model is started forwards and afterwards until the entire sequence is matched. Thirdly, a articulated 2D human body model is initialized from the matched template and then iteratively fit to the image features. Thus, the human body segmentation results and 2D body joints are got. Experiments are performed on broadcasted diving sequences and promising results are obtained. We also demonstrate two applications of the proposed method for sports training.