• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

Viewpoint Invariant Person Re-Identification for Global Multi-Object Tracking with Non-Overlapping Cameras

Vol. 11, No.4, April 30, 2017
10.3837/tiis.2017.04.014, Download Paper (Free):

Abstract

Person re-identification is to match pedestrians observed from non-overlapping camera views. It has important applications in video surveillance such as person retrieval, person tracking, and activity analysis. However, it is a very challenging problem due to illumination, pose and viewpoint variations between non-overlapping camera views. In this work, we propose a viewpoint invariant method for matching pedestrian images using orientation of pedestrian. First, the proposed method divides a pedestrian image into patches and assigns angle to a patch using the orientation of the pedestrian under the assumption that a person body has the cylindrical shape. The difference between angles are then used to compute the similarity between patches. We applied the proposed method to real-time global multi-object tracking across multiple disjoint cameras with non-overlapping field of views. Re-identification algorithm makes global trajectories by connecting local trajectories obtained by different local trackers. The effectiveness of the viewpoint invariant method for person re-identification was validated on the VIPeR dataset. In addition, we demonstrated the effectiveness of the proposed approach for the inter-camera multiple object tracking on the MCT dataset with ground truth data for local tracking.


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Cite this article

[IEEE Style]
Jeonghwan Gwak, Geunpyo Park and Moongu Jeon, "Viewpoint Invariant Person Re-Identification for Global Multi-Object Tracking with Non-Overlapping Cameras," KSII Transactions on Internet and Information Systems, vol. 11, no. 4, pp. 2075-2092, 2017. DOI: 10.3837/tiis.2017.04.014

[ACM Style]
Gwak, J., Park, G., and Jeon, M. 2017. Viewpoint Invariant Person Re-Identification for Global Multi-Object Tracking with Non-Overlapping Cameras. KSII Transactions on Internet and Information Systems, 11, 4, (2017), 2075-2092. DOI: 10.3837/tiis.2017.04.014