We present a scalable object tracking framework, which is capable of removing shadows and tracking the people. The framework consists of background subtraction, fuzzy based shadow removal and boundary tracking algorithm. This work proposes a general-purpose method that combines statistical assumptions with the object-level knowledge of moving objects, apparent objects, and shadows acquired in t...

Real time object detection and tracking is an important task in various computer vision applications. For robust object tracking the factors like object shape variation, partial and full occlusion, scene illumination variation will create significant problems. We introduce object detection and tracking approach that combines Prewitt edge detection and kalman filter. The target object’s represen...

Automatic detection and tracking of moving object is very important task for humancomputer interface (Black & Jepson, 1998), video communication/expression (Menser & Brunig, 2000), and security and surveillance system application (Greiffenhagen et al., 2000) and so on. Various imaging techniques for detection, tracking and identification of the moving objects have been proposed by many research...

This paper presents the first results obtained from the statistical object tracker developed at Duisburg University for the test data sequence provided by the organizers of the PETS2000 workshop. Our system differs from many other systems in that respect that it does not use any motion information at all for calculating the trajectory of a moving object in an image sequence, resulting in the fa...

Active contour models have proven to be a promising approach for data driven object tracking without knowledge about the problem domain and the object. Problems arise in case of fast moving objects and in natural scenes with heterogeneous background. In these cases, a prediction step is an essential part of the tracking mechanism. In this paper we describe a new approach for modelling the conto...

This paper presents the first results obtained from the statistical object tracker developed at Duisburg University for the test data sequence provided by the organizers of the PETS2000 workshop. Our system differs from many other systems in that respect that it does not use any motion information at all for calculating the trajectory of a moving object in an image sequence, resulting in the fa...

In this paper proposes new strategies for object tracking initialization using automatic moving object detection based background subtraction. The new strategies are integrated into the real-time object tracking system. The proposed background model updating technique and adaptive thresholding are used to produce a foreground object mask for object tracking initialization. Traditional backgroun...

Robust object tracking is required by many vision applications, and it will be useful for the motion analysis of moving object if we can not only track the object, but also make clear the corresponding relation of each part between consecutive frames. For this purpose, we propose a new method for moving object extraction and tracking based on the exclusive block matching. We build a cost matrix...