CONDENSATION—Conditional Density Propagation forVisual Tracking
International Journal of Computer Vision
Object Tracking with an Adaptive Color-Based Particle Filter
Proceedings of the 24th DAGM Symposium on Pattern Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust Real-Time Face Detection
International Journal of Computer Vision
Simultaneous Modeling and Tracking (SMAT) of Feature Sets
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Online Selection of Discriminative Tracking Features
IEEE Transactions on Pattern Analysis and Machine Intelligence
Incremental Learning for Robust Visual Tracking
International Journal of Computer Vision
Bittracker—A Bitmap Tracker for Visual Tracking under Very General Conditions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Hierarchical face tracking by using PTZ camera
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
An efficient continuous tracking system in real-time surveillance application
Journal of Network and Computer Applications
Efficient visual tracking using particle filter with incremental likelihood calculation
Information Sciences: an International Journal
GPS-based visual tracking for Pan/Tilt/Zoom camera in a ubiquitous camera environment
International Journal of Ad Hoc and Ubiquitous Computing
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We present here a real time active vision system on a PTZ network camera to track an object of interest. We address two critical issues in this paper. One is the control of the camera through network communication to follow a selected object. The other is to track an arbitrary type of object in real time under conditions of pose, viewpoint and illumination changes. We analyze the difficulties in the control through the network and propose a practical solution for tracking using a PTZ network camera. Moreover, we propose a robust real time tracking approach, which enhances the effectiveness by using complementary features under a two-stage particle filtering framework and a multi-scale mechanism. To improve time performance, the tracking algorithm is implemented as a multi-threaded process in OpenMP. Comparative experiments with state-of-the-art methods demonstrate the efficiency and robustness of our system in various applications such as pedestrian tracking, face tracking, and vehicle tracking.