Semantic Relational Object Tracking

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 match...

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Vydáno v:IEEE transactions on cognitive and developmental systems Ročník 12; číslo 1; s. 84 - 97
Hlavní autoři: Persson, Andreas, Zuidberg Dos Martires, Pedro, De Raedt, Luc, Loutfi, Amy
Médium: Journal Article
Jazyk:angličtina
Vydáno: Piscataway IEEE 01.03.2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Anchoring
Ground truth
Object Tracking
Perceptual Anchoring
Probabilistic Logic Programming
Probabilistic Reasoning
Reasoning
Relational Particle Filtering
Semantic World Modeling
Semantics
Tracking
ISSN:2379-8920, 2379-8939, 2379-8939
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Shrnutí: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, a high-level probabilistic object tracker has been integrated with the anchoring framework and handles the tracking of occluded objects via reasoning about the state of unobserved objects. We demonstrate the performance of our integrated approach through scenarios such as the shell game scenario, where we illustrate how anchored objects are retained by preserving relations through probabilistic reasoning.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
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ISSN:2379-8920
2379-8939
2379-8939
DOI:10.1109/TCDS.2019.2915763