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- W2103897188 abstract "A generic approach for tracking humans and objects under occlusion using semantic analysis is presented. The aim is to exploit knowledge representation schemes, precisely semantic logic where each detected object is represented by a node and the association among the nodes is interpretated as flow paths. Besides, maximum likelihood is computed using our CWHI technique and Bhattacharyya coefficient. These likelihood weights are mapped onto the semantic network to efficiently infer the multiple possibilities of tracking by the manipulation of “propositional logic” at a time window. The logical propositions are built by formularizing facts, semantic rules and constraints associated with tracking. Currently, we are able to handle tracking under normal, occlusion, and split conditions. The experimental results show that the proposed approach enables accurate and reliable tracking by resolving the ambiguities of online data association under occlusions." @default.
- W2103897188 created "2016-06-24" @default.
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- W2103897188 date "2009-09-01" @default.
- W2103897188 modified "2023-09-23" @default.
- W2103897188 title "Multi-object tracking using semantic analysis and Kalman filter" @default.
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- W2103897188 doi "https://doi.org/10.1109/ispa.2009.5297722" @default.
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