A framework for spatiotemporal control in the tracking of visual contours
International Journal of Computer Vision
Pfinder: Real-Time Tracking of the Human Body
IEEE Transactions on Pattern Analysis and Machine Intelligence
CONDENSATION—Conditional Density Propagation forVisual Tracking
International Journal of Computer Vision
Integrated Person Tracking Using Stereo, Color, and Pattern Detection
International Journal of Computer Vision - Special issue on a special section on visual surveillance
Detecting Faces in Images: A Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
Gesture recognition using the Perseus architecture
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
Elliptical Head Tracking Using Intensity Gradients and Color Histograms
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Detection of Skin Color under Changing Illumination: A Comparative Study
ICIAP '03 Proceedings of the 12th International Conference on Image Analysis and Processing
Skin Color-Based Video Segmentation under Time-Varying Illumination
IEEE Transactions on Pattern Analysis and Machine Intelligence
People detection and tracking using stereo vision and color
Image and Vision Computing
Multiple-person tracker with a fixed slanting stereo camera
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
People detection and tracking through stereo vision for human-robot interaction
MICAI'05 Proceedings of the 4th Mexican international conference on Advances in Artificial Intelligence
Visual capture and understanding of hand pointing actions in a 3-D environment
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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People detection and tracking are essential capabilities in human-robot interaction. However, the development of these tasks is specially difficult in cluttered environments where it is not possible to create a background model because of the robot movement. To detect and track people in a scene the use of vision sensors is convenient in order to distinguish people from other objects with similar shapes. This paper presents a novel approach for person tracking which combines depth, color and gradient information based on stereo vision. The degree of confidence assigned to depth information in the tracking process varies according to the amount of it found in the disparity map. A novel confidence measure is defined for it. To test the validity of our proposal, it is evaluated in several color-with-depth sequences where people interact in complex situations.