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The recently proposed covariance region descriptor has been proven robust and versatile for a modest computational cost. The covariance matrix enables efficient fusion of different types of features, where the spatial and statistical properties, as well as their correlation, are characterized. The similarity between two covariance descriptors is measured on Riemannian manifolds. Based on the same...
An appearance-based infrared target tracking method is proposed under the Kalman particle filter (KPF) framework. In the KPF, the Kalman filter, which can easily incorporate the observation into the state estimation, is used to generate the importance proposal distribution. Therefore, the KPF can be used to robustly track the infrared target against high-speed motion, irregular trajectory, low signal...
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...
Visual tracking is a challenging problem, as an object may change its appearance due to pose variations, illumination changes, and occlusions. Many algorithms have been proposed to update the target model using the large volume of available information during tracking, but at the cost of high computational complexity. To address this problem, we present a tracking approach that incrementally learns...
In this paper, a novel multi-cue collaborative kernel tracking algorithm is proposed. A new constraint based on the property of cross ratio invariant enables tracking of objects insensitive to complex motions, including scale changes, rotation and especially views changes, without labeling and training. Meanwhile, invariant moments are introduced into the kernel based tracking method as the shape...
Conventional video surveillance systems often have several shortcomings. First, target detection can't be accurate under the light variation environment or clustering backgrounds. Second, multiple targets tracking become difficult on a crowd scene because the split and merge or occlusions among the tracked targets occur frequently and irregularly. Third, it is difficult to the partition the tracked...
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