3D Reconstruction of freely moving persons for re-identification with a depth sensor
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Date
2014
Publication Type
Conference Paper
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yes
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Abstract
In this work, we describe a novel method for creating 3D models of persons freely moving in front of a consumer depth sensor and we show how they can be used for long-term person re-identification. For overcoming the problem of the different poses a person can assume, we exploit the information provided by skeletal tracking algorithms for warping every point cloud frame to a standard pose in real time. Then, the warped point clouds are merged together to compose the model. Re-identification is performed by matching body shapes in terms of whole point clouds warped to a standard pose with the described method. We compare this technique with a classification method based on a descriptor of skeleton features and with a mixed approach which exploits both skeleton and shape features. We report experiments on two datasets we acquired for RGB-D re-identification which use different skeletal tracking algorithms and which are made publicly available to foster research in this new research branch.
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published
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Book title
2014 IEEE International Conference on Robotics and Automation (ICRA)
Journal / series
Volume
6
Pages / Article No.
4512 - 4519
Publisher
IEEE
Event
IEEE International Conference on Robotics and Automation (ICRA 2014)
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Methods
Software
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03514 - Van Gool, Luc (emeritus) / Van Gool, Luc (emeritus)