Skip to Main content Skip to Navigation
Conference papers

ODANet: Online Deep Appearance Network for Identity-Consistent Multi-Person Tracking

Guillaume Delorme 1, 2 Yutong Ban 3, 1 Guillaume Sarrazin 1 Xavier Alameda-Pineda 1, 2 
1 PERCEPTION - Interpretation and Modelling of Images and Videos
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology
Abstract : The analysis of effective states through time in multi-person scenarii is very challenging, because it requires to consistently track all persons over time. This requires a robust visual appearance model capable of re-identifying people already tracked in the past, as well as spotting newcomers. In real-world applications, the appearance of the persons to be tracked is unknown in advance, and therefore on must devise methods that are both discriminative and flexible. Previous work in the literature proposed different tracking methods with fixed appearance models. These models allowed, up to a certain extent, to discriminate between appearance samples of two different people. We propose an online deep appearance network (ODANet), a method able to simultaneously track people and update the appearance model with the newly gathered annotation-less images. Since this task is specially relevant for autonomous systems, we also describe a platform-independent robotic implementation of ODANet. Our experiments show the superiority of the proposed method with respect to the state of the art, and demonstrate the ability of ODANet to adapt to sudden changes in appearance, to integrate new appearances in the tracking system and to provide more identity-consistent tracks.
Complete list of metadata
Contributor : Xavier Alameda-Pineda Connect in order to contact the contributor
Submitted on : Wednesday, January 26, 2022 - 11:36:57 AM
Last modification on : Thursday, March 31, 2022 - 12:05:16 PM


Files produced by the author(s)



Guillaume Delorme, Yutong Ban, Guillaume Sarrazin, Xavier Alameda-Pineda. ODANet: Online Deep Appearance Network for Identity-Consistent Multi-Person Tracking. ICPR 2021 - 25th International Conference on Pattern Recognition / Workshops, Jan 2021, Milano / Virtual, Italy. pp.803-818, ⟨10.1007/978-3-030-68780-9_60⟩. ⟨hal-03188744v2⟩



Record views


Files downloads