Paper
18 March 2005 Towards a multilevel cognitive probabilistic representation of space
Adriana Tapus, Shrihari Vasudevan, Roland Siegwart
Author Affiliations +
Proceedings Volume 5666, Human Vision and Electronic Imaging X; (2005) https://doi.org/10.1117/12.594487
Event: Electronic Imaging 2005, 2005, San Jose, California, United States
Abstract
This paper addresses the problem of perception and representation of space for a mobile agent. A probabilistic hierarchical framework is suggested as a solution to this problem. The method proposed is a combination of probabilistic belief with “Object Graph Models”(OGM). The world is viewed from a topological optic, in terms of objects and relationships between them. The hierarchical representation that we propose permits an efficient and reliable modeling of the information that the mobile agent would perceive from its environment. The integration of both navigational and interactional capabilities through efficient representation is also addressed. Experiments on a set of images taken from the real world that validate the approach are reported. This framework draws on the general understanding of human cognition and perception and contributes towards the overall efforts to build cognitive robot companions.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Adriana Tapus, Shrihari Vasudevan, and Roland Siegwart "Towards a multilevel cognitive probabilistic representation of space", Proc. SPIE 5666, Human Vision and Electronic Imaging X, (18 March 2005); https://doi.org/10.1117/12.594487
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Cited by 10 scholarly publications.
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KEYWORDS
Object recognition

RGB color model

Data modeling

Cognitive modeling

Feature extraction

3D modeling

Animal model studies

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