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Full-Text Articles in Physical Sciences and Mathematics
Near-Duplicate Keyframe Retrieval By Semi-Supervised Learning And Nonrigid Image Matching, Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu, Shuicheng Yan
Near-Duplicate Keyframe Retrieval By Semi-Supervised Learning And Nonrigid Image Matching, Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu, Shuicheng Yan
Research Collection School Of Computing and Information Systems
Near-duplicate keyframe (NDK) retrieval techniques are critical to many real-world multimedia applications. Over the last few years, we have witnessed a surge of attention on studying near-duplicate image/keyframe retrieval in multimedia community. To facilitate an effective approach to NDK retrieval on large-scale data, we suggest an effective Multi-Level Ranking (MLR) scheme that effectively retrieves NDKs in a coarse-to-fine manner. One key stage of the MLR ranking scheme is how to learn an effective ranking function with extremely small training examples in a near-duplicate detection task. To attack this challenge, we employ a semi-supervised learning method, semi-supervised support vector machines, which …
Near-Duplicate Keyframe Retrieval By Nonrigid Image Matching, Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu, Shuicheng Yan
Near-Duplicate Keyframe Retrieval By Nonrigid Image Matching, Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu, Shuicheng Yan
Research Collection School Of Computing and Information Systems
Near-duplicate image retrieval plays an important role in many real-world multimedia applications. Most previous approaches have some limitations. For example, conventional appearance-based methods may suffer from the illumination variations and occlusion issue, and local feature correspondence-based methods often do not consider local deformations and the spatial coherence between two point sets. In this paper, we propose a novel and effective Nonrigid Image Matching (NIM) approach to tackle the task of near-duplicate keyframe retrieval from real-world video corpora. In contrast to previous approaches, the NIM technique can recover an explicit mapping between two near-duplicate images with a few deformation parameters and …
An Effective Approach To 3d Deformable Surface Tracking, Jianke Zhu, Steven C. H. Hoi, Zenglin Xu, Michael R. Lyu
An Effective Approach To 3d Deformable Surface Tracking, Jianke Zhu, Steven C. H. Hoi, Zenglin Xu, Michael R. Lyu
Research Collection School Of Computing and Information Systems
The key challenge with 3D deformable surface tracking arises from the difficulty in estimating a large number of 3D shape parameters from noisy observations. A recent state-of-the-art approach attacks this problem by formulating it as a Second Order Cone Programming (SOCP) feasibility problem. The main drawback of this solution is the high computational cost. In this paper, we first reformulate the problem into an unconstrained quadratic optimization problem. Instead of handling a large set of complicated SOCP constraints, our new formulation can be solved very efficiently by resolving a set of sparse linear equations. Based on the new framework, a …