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3D Reconstruction of freely moving persons for re-identification with a depth sensor

M. Munaro, A. Basso, A. Fossati, L. Van Gool and E. Menegatti
IEEE International Conference on Robotics and Automation (ICRA)
Hong Kong, June 2014

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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@InProceedings{eth_biwi_01074,
  author = {M. Munaro and A. Basso and A. Fossati and L. Van Gool and E. Menegatti},
  title = {3D Reconstruction of freely moving persons for re-identification with a depth sensor},
  booktitle = {IEEE International Conference on Robotics and Automation (ICRA)},
  year = {2014},
  month = {June},
  keywords = {}
}