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Multi-target tracking plays a key role in many computer vision applications including robotics, human-computer interaction, event recognition, etc., and has received increasing attention in past several years. Starting with an object detector is one of many approaches used by existing multi-target tracking methods to create initial short tracks called tracklets. These tracklets are then gradually...
Reliably measuring the similarity of two shapes or images (instances) is an important problem for various computer vision applications such as classification, recognition, and retrieval. While pairwise measures take advantage of the geometric differences between two instances to quantify their similarity, recent advances use relationships among the population of instances when quantifying pairwise...
The major challenge in constructing a statistical shape model for a structure is shape correspondence, which identifies a set of corresponded landmarks across a population of shape instances to accurately estimate the underlying shape variation. Both global or pairwise shape-correspondence methods have been developed to automatically identify the corresponded landmarks. For global methods, landmarks...
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