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In object detection, disparities in distributions between the training samples and the test ones are often inevitable, resulting in degraded performance for application scenarios. In this paper, we focus on the disparities caused by viewpoint and scene changes and propose an efficient solution to these particular cases by adapting generic detectors, assuming boosting style. A pretrained boosting-style...
This paper presents a framework to track non-rigid objects adaptively by fusion of visual and motional feature descriptors. The proposed technique can automatically detect an object from different points of view as soon as the object starts moving. Moreover an object model is created and gradually updated using both new and previous features. As a result, the proposed technique is able to track a...
An integrated technology of top-down and bottom-up visual attention used to the solution of the feature selection and saliency detection problems in object extraction and categorization of natural scene images is proposed. A decision criterion based on the top-down, goal-driven component is introduced to select the features of desired detection object which best distinguish the object from the other...
When people take videos, they always want to capture intended objects, which are essential for presenting what they want to express in their videos, and to share the intended objects with others. The concept of intended objects provide a novel perspective for video content analysis, and detecting intended objects may be beneficial for wide range of applications such as video understanding and semantics...
Although primates can facilely maintain long-duration tracking of an object without infection of occlusion or other near similar distracters, it remains a challenge for computer vision system. Studies in psychology suggest that the ability of primates to focus selective attention on the spatial properties of an object is necessary to observe object quickly and efficiently while focus selective attention...
A new algorithm is proposed for background subtraction in highly dynamic scenes. Background subtraction is equated to the dual problem of saliency detection: background points are those considered not salient by suitable comparison of object and background appearance and dynamics. Drawing inspiration from biological vision, saliency is defined locally, using center-surround computations that measure...
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