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Clustered features for use in stereo vision SLAM

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dc.contributor.author Joubert, D
dc.date.accessioned 2010-10-25T11:31:03Z
dc.date.available 2010-10-25T11:31:03Z
dc.date.issued 2010-07
dc.identifier.citation Joubert, D. 2010. Clustered features for use in stereo vision SLAM. Proceedings of the 25th International Conference of CAD/CAM, Robotics & Factories of the Future Conference, CSIR International Convention Centre, Pretoria, South Africa, 13-16 July 2010, pp 7 en
dc.identifier.isbn 9780620465823
dc.identifier.uri http://hdl.handle.net/10204/4499
dc.description Proceedings of the 25th International Conference of CAD/CAM, Robotics & Factories of the Future Conference, CSIR International Convention Centre, Pretoria, South Africa, 13-16 July 2010 en
dc.description.abstract SLAM, or simultaneous localization and mapping, is a key component in the development of truly independent robots. Vision-based SLAM utilising stereo vision is a promising approach to SLAM but it is computationally expensive and difficult to implement. New feature manipulation techniques are proposed which incorporate relational and positional information of the features into the extraction and data association steps. en
dc.language.iso en en
dc.relation.ispartofseries Conference Paper en
dc.subject Stereo vision en
dc.subject Machine vision en
dc.subject SLAM en
dc.subject Feature extraction en
dc.subject Data association en
dc.subject Robotics en
dc.title Clustered features for use in stereo vision SLAM en
dc.type Conference Presentation en
dc.identifier.apacitation Joubert, D. (2010). Clustered features for use in stereo vision SLAM. http://hdl.handle.net/10204/4499 en_ZA
dc.identifier.chicagocitation Joubert, D. "Clustered features for use in stereo vision SLAM." (2010): http://hdl.handle.net/10204/4499 en_ZA
dc.identifier.vancouvercitation Joubert D, Clustered features for use in stereo vision SLAM; 2010. http://hdl.handle.net/10204/4499 . en_ZA
dc.identifier.ris TY - Conference Presentation AU - Joubert, D AB - SLAM, or simultaneous localization and mapping, is a key component in the development of truly independent robots. Vision-based SLAM utilising stereo vision is a promising approach to SLAM but it is computationally expensive and difficult to implement. New feature manipulation techniques are proposed which incorporate relational and positional information of the features into the extraction and data association steps. DA - 2010-07 DB - ResearchSpace DP - CSIR KW - Stereo vision KW - Machine vision KW - SLAM KW - Feature extraction KW - Data association KW - Robotics LK - https://researchspace.csir.co.za PY - 2010 SM - 9780620465823 T1 - Clustered features for use in stereo vision SLAM TI - Clustered features for use in stereo vision SLAM UR - http://hdl.handle.net/10204/4499 ER - en_ZA


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