Geometric invariance in computer vision
Geometric invariance in computer vision
Computer graphics (2nd ed.)
Intelligent scissors for image composition
SIGGRAPH '95 Proceedings of the 22nd annual conference on Computer graphics and interactive techniques
Pfinder: Real-Time Tracking of the Human Body
IEEE Transactions on Pattern Analysis and Machine Intelligence
The NURBS book (2nd ed.)
CONDENSATION—Conditional Density Propagation forVisual Tracking
International Journal of Computer Vision
Robust Tracking of Position and Velocity With Kalman Snakes
IEEE Transactions on Pattern Analysis and Machine Intelligence
Human motion analysis: a review
Computer Vision and Image Understanding
Learning Patterns of Activity Using Real-Time Tracking
IEEE Transactions on Pattern Analysis and Machine Intelligence
Real-Time Tracking of Moving Persons by Exploiting Spatio-Temporal Image Slices
IEEE Transactions on Pattern Analysis and Machine Intelligence
Tracking persons in monocular image sequences
Computer Vision and Image Understanding
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
Epipolar Geometry in Stereo, Motion, and Object Recognition: A Unified Approach
Epipolar Geometry in Stereo, Motion, and Object Recognition: A Unified Approach
B-spline Contour Representation and Symmetry Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Model-based estimation of 3D human motion with occlusion based on active multi-viewpoint selection
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
Tracking through Singularities and Discontinuities by Random Sampling
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
| Hi-index | 0.00 |
In this paper the idea of Intelligent Scissors is adopted for contour tracking in dynamic image sequence. Tracking contour of human can therefore be converted to tracking seed points in images by making use of the properties of the optimal path (Intelligent Edge). The main advantage of the approach is that it can handle correctly occlusions that occur frequently when human is moving. Non-Uniform Rational B-Spline (NURBS) is used to represent parametrically the contour that one wants to track. In order to track robustly the contour in images, similarity and compatibility measurements of the edge are computed as the weighting functions of optimal estimator. To reduce dramatically the computational load, an efficient method for extracting the region interested is proposed. Experiments show that the approach works robustly for sequences with frequent occlusions.