Real-time multi-object tracking with occlusion and stationary objects handling for conveying systems

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Abstract

Multiple object tracking has a broad range of applications ranging from video surveillance to robotics. In this work, we extend the application field to automated conveying systems. Inspired by tracking methods applied to video surveillance, we follow an on-line tracking-by-detection approach based on background subtraction. The logistics applications turn out to be a challenging scenario for existing methods. This challenge is twofold: First, conveyed objects tend to have a similar appearance, which makes the occlusion handling difficult. Second, they are often stationary, which make them hard to detect with background subtraction techniques. This work aims to improve the occlusion handling by using the order of the conveyed objects. Besides, to handle stationary objects, we propose a feedback loop from tracking to detection. Finally, we provide an evaluation of the proposed method on a real-world video.

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Benamara, A., Miguet, S., & Scuturici, M. (2016). Real-time multi-object tracking with occlusion and stationary objects handling for conveying systems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10072 LNCS, pp. 136–145). Springer Verlag. https://doi.org/10.1007/978-3-319-50835-1_13

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