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Local features have been widely used in many computer vision related researches, such as near-duplicate image and video retrieval. However, the storage and query cost of local features become prohibitive on large-scale database. In this paper, we propose a representative local features mining method to generate a compact but more effective feature subset. First, we do an unsupervised annotation for...
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...
We propose an improved fusion method used in high level feature extraction at TRECVID - average precision based Adaboost (AP-based Adaboost). The AP-based weighting scheme makes use of both the weight and the rank of each sample that all have contribution to the final average precision. The weighting scheme along with the more adaptive formulae modified in our method makes it outperform the standard...
With the extensive application of digital video technology, developing format-independent motion describing method is of great significance for retrieving and searching video content in different formats. In this paper, a format-independent motion describing method for video content is proposed. The features based on visual sensitivity are extracted from spatiotemporal slice. Since the same video...
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