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This paper presents a novel framework for activities perception in video surveillance scenarios. Firstly, moving objects are detected by modeling the background using Gaussian Mixture Model (GMM). Secondly, a novel adaptive particle filter (APF) is introduced. The proposed APF has time-varying dimensions and can track multiple moving objects entering or leaving the field of view effectively. Finally,...
With the rapid development of computer vision and intelligent recognition, real-time alarm analysis of surveillance system has become possible. In this paper, a system for the detection of object entering into prohibited area in surveillance video is designed based on the moving object detection and tracking technology. For motion detection, the Gaussian Mixture Model with background segmentation...
The problem of tracking general objects is still challenging. Particle filter is inadequate in many cases because the results often contain nothing more than the trajectories of moving objects and no contour information is involved. We propose a new method, the Oriented Particle Filter. Our method employs the Gaussian Mixture Model to represent the object, and incorporates spatial cues by assigning...
In this paper we present a segmentation system for monocular video sequences with static camera that aims at foreground/background separation and tracking. We propose to combine a simple pixel-wise model for the background with a general purpose region based model for the foreground. The background is modeled using one Gaussian per pixel, thus achieving a precise and easy to update model. The foreground...
One of the challenges to creating robust trackers is the construction of robust appearance Model. This paper presents a robust appearance model for object tracking. The robust object distribution is acquired by comparing the two Gaussian Mixture Models of the object and background. The probability image generated by the robust object distribution is used for the CAMSHIFT tracking. Experiments on several...
Aiming at improving the performance of non-rigid object tracking in video sequences acquired by a stationary camera, an effective method based on the adaptive color segmentation and object part model was presented. In this work, we modeled background and obtained the foreground blobs with an effective adaptive background updating method based on Gaussian mixture model (GMM), and then the regions in...
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