Learn More
Visual tracking in unconstrained environments is very challenging due to the existence of several sources of varieties such as changes in appearance, varying lighting conditions , cluttered background, and frame-cuts. A major factor causing tracking failure is the emergence of regions having similar appearance as the target. It is even more challenging when(More)
Visual tracking is a challenging problem, as an object may change its appearance due to viewpoint variations, illumination changes, and occlusion. Also, an object may leave the field of view and then reappear. In order to track and reacquire an unknown object with limited labeling data, we propose to learn these changes online and build a model that(More)
Skin color is one of most important source of information widely used in Human-Computer Interaction (HCI) system where detecting the presence of the human plays a key role. It is because of the dynamics and articulations of human body which is hard to be captured rather than using primitive feature like skin color. However, skin color varies across(More)
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(More)
— We propose here to acquire high resolution sequences of a person's face using a pan-tilt-zoom (PTZ) network camera. This capability should prove helpful in forensic analysis of video sequences as frames containing faces are tagged, and within a frame, windows containing faces can be retrieved. The system starts in pedestrian detector mode, where the lens(More)
Partial occlusion is a challenging problem in object tracking. In online visual tracking, it is the critical factor causing drift. To address this problem, we propose a novel approach using a co-training framework of generative and discriminative trackers. Our approach is able to detect the occluding region and continuously update both the generative and(More)
We address the problem of automatic face detection and tracking in uncontrolled scenarios using a pan-tilt-zoom (PTZ) network camera, which could prove most helpful in forensic applications. The detected faces are associated with the corresponding people and trajectories. The dynamic nature of real-world scenarios and real-time restrictions complicate our(More)