A decision-theoretic generalization of on-line learning and an application to boosting
Journal of Computer and System Sciences - Special issue: 26th annual ACM symposium on the theory of computing & STOC'94, May 23–25, 1994, and second annual Europe an conference on computational learning theory (EuroCOLT'95), March 13–15, 1995
Efficient Region Tracking With Parametric Models of Geometry and Illumination
IEEE Transactions on Pattern Analysis and Machine Intelligence
CONDENSATION—Conditional Density Propagation forVisual Tracking
International Journal of Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Integrated Person Tracking Using Stereo, Color, and Pattern Detection
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Bilateral Filtering for Gray and Color Images
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
Robotics and Autonomous Systems
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This paper introduces a method for face tracking in a video sequence in real time. In this method the profile of color distribution characterizes target's feature. It is invariant for rotation and scale changes. It's also robust to non-rigidity and partial occlusion of the target. We employ the mean-shift algorithm to track the target face and to reduce the computational cost. However, face tracking using color distribution is failed by noises as occlusion including some objects with similar color distribution and with exactly difference color distribution. Thus failures are critical problems. To solve these problems, we employ a bilateral filter which uses the color and range information. We have applied the proposed bilateral filter to track the real time face tracking. The experimental results demonstrate the efficiency of this algorithm. Its performance has been proven superior to the original mean shift tracking algorithm.