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We propose a promising method of geometric verification to improve the precision of Bag-of-Words (BoW) model in image retrieval. Most previous methods focus on the positions of interest points or the absolute differences of regions' scales and angles. In contrast, our method, named Region Similarity Arrangement (RSA), exploits the spatial arrangement of interest regions. For each image, RSA constructs...
Scrambling is widely used to protect privacy in surveillance video. However, as a critical issue in privacy protected video scrambling, drift error has not been adequately studied. In this paper, we focus on drift error prevention for different elements scrambling in privacy protected H.264/AVC video, which is the prevailing coding standard. A restricted coding scheme is proposed to prevent drift...
Spatial matching for object retrieval is often time-consuming and susceptible to viewpoint changes. To address this problem, we propose a novel spatial matching method and implement it on modern GPU in parallel. Unlike previous spatial matching methods, in which the affine transformation estimation is based on the gravity vector assumption, our method abandons this strong assumption by matching the...
Spatial matching for visual words based object retrieval often involves generating affine transformation hypotheses and then choosing the best hypothesis to measure the spatial consistency. In existing methods, generating an affine transformation hypothesis either requires three correspondences or assumes images are taken in restricted range of viewpoints in using a single correspondence. In this...
Effective feature extraction is a fundamental component of content-based image retrieval. Scale Invariant Feature Transform (SIFT) has been proven to be the most robust local invariant feature descriptor. However, SIFT algorithm generates hundreds of thousands of keypoints per image, and most of them comes from background. This has seriously affected the application of SIFT in real-time image retrieval...
A new method is proposed for highlight extraction in soccer videos based on goal-mouth detection. This approach is based on the observations that the appearance of goal-mouth points to a high likelihood of exciting action in soccer videos and that highlight is composed of certain types of scene views which exhibit certain transition rules. To exploit those observations, first goal-mouth are detected...
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