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Semantic Relational Object Tracking
IEEE Transactions on Cognitive and Developmental Systems
This paper addresses the topic of semantic world modeling by conjoining probabilistic reasoning and object anchoring. The proposed approach uses a so-called bottom-up object anchoring method that relies on rich continuous attribute values measured from perceptual sensor data. A novel anchoring matching function learns to maintain object entities in space and time and is validated using a large set of trained humanly annotated ground truth data of real-world objects. For more complex scenarios,doi:10.1109/tcds.2019.2915763 fatcat:qqkmjezxpvecvo4hm5t5k7wdcu