International Journal of Computer Vision
Pfinder: Real-Time Tracking of the Human Body
IEEE Transactions on Pattern Analysis and Machine Intelligence
Mean Shift, Mode Seeking, and Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Object Recognition Using Multidimensional Receptive Field Histograms
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume I - Volume I
Color-Based Tracking of Heads and Other Mobile Objects at Video Frame Rates
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Elliptical Head Tracking Using Intensity Gradients and Color Histograms
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Multi-Modal System for Locating Heads and Faces
FG '96 Proceedings of the 2nd International Conference on Automatic Face and Gesture Recognition (FG '96)
Real Time Face and Object Tracking as a Component of a Perceptual User Interface
WACV '98 Proceedings of the 4th IEEE Workshop on Applications of Computer Vision (WACV'98)
Nonparametric robust methods for computer vision
Nonparametric robust methods for computer vision
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A new method is presented for tracking a person's head in real-time. The head is shaped as an ellipse, and the adaptively modified RGB color histogram is used to represent the tacked object (head). The method is composed of two parts. First, a robust nonparametrlc technique, called mean shift algorithm, is adopted for histogram matching to estimate the head's location in the current frame. Second, a local search is performed after histogram matching to maximize the normalized gradient magnitude around the boundary of the elliptical head, so that a more accurate location and the best scale size of the head can be obtained. The method is demonstrated to be a real-time tracker and robust to clutter, scale variation, occlusion, rotation and camera motion, for several test sequences.