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Visual feature descriptors have been successfully deployed in a wide range of applications, e.g. visual retrieval and analysis. To transmit these descriptors over bandwidth-limited networks, a high effciency feature coding technique is highly desired to maximize compression capability and achieve compact feature representations. In this paper, a hybrid visual feature descriptor compression framework...
Canonical correlation analysis (CCA) has been widely used in pattern recognition and machine learning. However, both CCA and its extensions sometimes cannot give satisfactory results. In this paper, we propose a new CCA-type method termed sparse representation based discriminative CCA (SPDCCA) by incorporating sparse representation and discriminative information simultaneously into traditional CCA...
Detailed geometric modeling from images is very important but extremely complex and computationally expensive. In this paper we present an algorithm for large-scale urban terrestrial geometric modeling from videos. In the proposed approach, we classify and segment the contents of images based on the knowledge about the scene. Then the segments of each image are aligned to similar segments of the consecutive...
Robust foreground segmentation is an essential step in many computer vision applications such as visual surveillance and behavior analysis. This paper proposes a subspace based background modeling and foreground segmentation algorithm, which improves the incremental background subspace learning in a robust manner. It can efficiently reduce the influence of the foreground pixels which are undesired...
The research on digital visible human is of great significance and application value. The US Visible Human Project (VHP) created the first digital image data set of a complete human (one male and one female) in 1995. To promote a worldwide application-oriented VHR, more visible human data sets representative of different populations of the world are in demand. The Chinese Visible Human (CVH) male...
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