A survey of computer vision-based human motion capture
Computer Vision and Image Understanding - Modeling people toward vision-based underatanding of a person's shape, appearance, and movement
Contour Tracking by Stochastic Propagation of Conditional Density
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume I - Volume I
Stochastic Tracking of 3D Human Figures Using 2D Image Motion
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part II
Cardboard People: A Parameterized Model of Articulated Image Motion
FG '96 Proceedings of the 2nd International Conference on Automatic Face and Gesture Recognition (FG '96)
Moving Target Classification and Tracking from Real-time Video
WACV '98 Proceedings of the 4th IEEE Workshop on Applications of Computer Vision (WACV'98)
Model Based Extraction of Articulated Objects in Image Sequences for Gait Analysis
ICIP '97 Proceedings of the 1997 International Conference on Image Processing (ICIP '97) 3-Volume Set-Volume 3 - Volume 3
| Hi-index | 0.00 |
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.