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• W2743304845 abstract "Despite many proposed solutions, multi-object tracking remains a challenging problem in complex situations involving partial occlusions and non-uniform and abrupt illumination changes. Considering modular systems, the tracking performance strongly depends on the consistency of the different blocks relatively to error features. In this work, using the Belief Function framework, we take into account the reliability and the imprecision of the object detection and location to characterize objects and to derive a reliable descriptor. Since this latter is then estimated only on safe object subparts, even in case of crosses between objects, we use a distance between descriptor robust to partial occlusion, namely the recently proposed Bin-Ratio-Distance. Results obtained on various actual sequences underline the interest of the proposed algorithm by outperforming the tested alternative approaches." @default.
• W2743304845 created "2017-08-17" @default.
• W2743304845 creator A5055435924 @default.
• W2743304845 creator A5066496994 @default.
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• W2743304845 date "2017-07-01" @default.
• W2743304845 modified "2023-10-12" @default.
• W2743304845 title "A novel approach for multi-object tracking using evidential representation for objects" @default.
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• W2743304845 doi "https://doi.org/10.23919/icif.2017.8009819" @default.
• W2743304845 hasPublicationYear "2017" @default.
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