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Real-Time and Online Segmentation Multi-Target Tracking with Track Revival Re-Identification

Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, 2021, Vol.5, p.777

ISBN: 9789897584886 ;ISBN: 9897584889 ;DOI: 10.5220/0010190907770784

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  • Title:
    Real-Time and Online Segmentation Multi-Target Tracking with Track Revival Re-Identification
  • Author: Ahrnbom, Martin ; Nilsson, Mikael ; Ardö, Håkan
  • Subjects: Computer and Information Science ; Computer Vision and Robotics (Autonomous Systems) ; Data- och informationsvetenskap (Datateknik) ; Datorseende och robotik (autonoma system) ; Natural Sciences ; Naturvetenskap
  • Is Part Of: Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, 2021, Vol.5, p.777
  • Description: The first online segmentation multi-target tracking algorithm with reported real-time speeds is presented. Based on the popular and fast bounding box based tracker SORT, our method called SORTS is able to utilize segmentations for tracking while keeping the real-time speeds. To handle occlusions, which neither SORT nor SORTS do, we also present SORTS+RReID, an optional extension which uses ReID vectors to revive lost tracks from SORTS to handle occlusions. Despite only computing ReID vectors for 6.9% of the detections, ID switches are decreased by 45%. We evaluate on the MOTS dataset and run at 54.5 and 36.4 FPS for SORTS and SORT+RReID respectively, while keeping 78-79% of the sMOTSA of the current state of the art, which runs at 0.3 FPS. Furthermore, we include an experiment using a faster instance segmentation method to explore the feasibility of a complete real-time detection and tracking system. Code is available: https://github.com/ahrnbom/sorts.
  • Language: Swedish
  • Identifier: ISBN: 9789897584886
    ISBN: 9897584889
    DOI: 10.5220/0010190907770784
  • Source: SWEPUB Freely available online
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