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Vision based computation of the moving CCD camera in an outdoor environment is one of the most difficult tasks in the computer vision (CV) research field. Currently, to implement only one CV function steadily, one even needs to develop a series of algorithms to meet the computational requirement of the complex environment change inevitably. So the choice of the switch occasion of these different algorithms...
In this paper, we propose a novel approach that combines particle filter tracking and 3D graph cut based segmentation to achieve silhouette tracking against drastic scale change and occlusion. The segmentation module offers particle filter tracking procedure the target shape information to compensate spatial information loss in the histogram based particle filter tracking process. Meanwhile, particle...
Under a complex atmosphere, the visibility of images captured by a moving camera needs to be enhanced so as to overcome various atmospheric perturbations. To achieve a stable and robust performance, in this paper, we propose to build a time series based model in wavelet domain by employing both spatial and temporal information of the sequential images. First, we set up a blind evaluation criteria...
In this paper, we present a novel approach for human activities recognition in the video. We analyze human activities in the sequential frames because human activities can be considered as a temporal object which contains a series of frames. Firstly, we establish a statistical background model and extract foreground object through background subtraction in the video stream. Then, we use foreground...
This paper propose a novel algorithm, the trust region embedded particle filter (TREPF), for target tracking in infrared imagery. Trust regions and particle filters are two successful methods for object tracking. The presented TREPF algorithm integrates the advantages of the two approaches. Contrasting the original particle filters and trust regions, the new algorithm can maintain multiple hypotheses...
In this paper we study the problem of local motion analysis and apply it to swimming style recognition in broadcast sports video. Local motion analysis is challenging for two reasons: 1) local motion is usually buried in clutters involving complex motion from multiple objects; and 2) the process is more sensitive to noises compared to the recovery of global motion. However, an effective approach to...
This paper presents a novel algorithm named diverse AdaBoostSVM tracking (DABSVT) for target tracking in infrared imagery. The tracker trains a support vector machine (SVM) classifier per frame. All of the classifiers are combined into an ensemble classifier using AdaBoost. By proper parameter adjusting strategies, a set of effective SVM classifiers with moderate accuracy are obtained, and the dilemma...
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