Mean Shift: A Robust Approach Toward Feature Space Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Color-Based Probabilistic Tracking
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient Mean-Shift Tracking via a New Similarity Measure
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Multiple Object Tracking with Kernel Particle Filter
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Online Selection of Discriminative Tracking Features
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic Feature-Based Face Scoring in Surveillance Systems
ISM '07 Proceedings of the Ninth IEEE International Symposium on Multimedia
Antiextensive connected operators for image and sequence processing
IEEE Transactions on Image Processing
Object recognition and tracking for remote video surveillance
IEEE Transactions on Circuits and Systems for Video Technology
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Local appearance of object is of importance to content analysis, object recognition and forensic authentication. However, existing video surveillance systems are almost incapable of capturing local appearance of object in a remote scene. We present a video surveillance system in dealing with object tracking and local appearance capturing in a remote scene, which consists of one pan&tilt and two cameras with different focuses. One camera has short focus lens for object tracking while the other has long ones for local appearance capturing. Video object can be located via just one manual selection or motion detection, which is switched into a modified kernel-based tracking algorithm absorbing both color value and gradient distribution. Meanwhile, local appearance of object such as face is captured via long focus camera. Both simulated and real-time experiments of the proposed system have achieved promising results.