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Landscape mapping MAV using single image perspective cues

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dc.contributor.author Tekane, YC
dc.contributor.author Twala, B
dc.contributor.author Marwala, T
dc.date.accessioned 2015-10-05T07:21:24Z
dc.date.available 2015-10-05T07:21:24Z
dc.date.issued 2015-01
dc.identifier.citation Tekane, YC, Twala, B and Marwala, T. 2015. Landscape mapping MAV using single image perspective cues. In: International Conference on Mechatronics and Robotics Engineering (ICMRE 2015), Kuala Lumpur, 17-18 January 2015, 9pp. en_US
dc.identifier.uri http://hdl.handle.net/10204/8144
dc.description International Conference on Mechatronics and Robotics Engineering (ICMRE 2015), Kuala Lumpur, 17-18 January 2015 en_US
dc.description.abstract We consider the problem of mapping with Miniature Aerial Vehicles (MAVs) in outdoor sites with distinguishable landscapes. The primary long range sensor in these MAVs is a miniature camera. While previous approaches first try to build a 3D model in order to do mapping, our method does require a 3D model. Instead, our method first classifies the type of site the MAV is in, and the uses vision algorithms based on perspective cues to estimate the landscape location and the do mapping. We tested our method on a number of sites with different landscapes. Our experiments show that our vision algorithms are reliable, and the enable the MAV to identify landscapes and map them. en_US
dc.language.iso en en_US
dc.relation.ispartofseries Worklist;15528
dc.subject Miniature Aerial Vehicles en_US
dc.subject MAVs en_US
dc.subject Landscape mapping en_US
dc.subject Vanishing point en_US
dc.subject Vision algorithm en_US
dc.subject Hough transforms en_US
dc.subject Miniature aerial vehicle en_US
dc.subject Canny edge detector en_US
dc.subject Perspective cue en_US
dc.subject Graph SLAM en_US
dc.title Landscape mapping MAV using single image perspective cues en_US
dc.type Conference Presentation en_US
dc.identifier.apacitation Tekane, Y., Twala, B., & Marwala, T. (2015). Landscape mapping MAV using single image perspective cues. http://hdl.handle.net/10204/8144 en_ZA
dc.identifier.chicagocitation Tekane, YC, B Twala, and T Marwala. "Landscape mapping MAV using single image perspective cues." (2015): http://hdl.handle.net/10204/8144 en_ZA
dc.identifier.vancouvercitation Tekane Y, Twala B, Marwala T, Landscape mapping MAV using single image perspective cues; 2015. http://hdl.handle.net/10204/8144 . en_ZA
dc.identifier.ris TY - Conference Presentation AU - Tekane, YC AU - Twala, B AU - Marwala, T AB - We consider the problem of mapping with Miniature Aerial Vehicles (MAVs) in outdoor sites with distinguishable landscapes. The primary long range sensor in these MAVs is a miniature camera. While previous approaches first try to build a 3D model in order to do mapping, our method does require a 3D model. Instead, our method first classifies the type of site the MAV is in, and the uses vision algorithms based on perspective cues to estimate the landscape location and the do mapping. We tested our method on a number of sites with different landscapes. Our experiments show that our vision algorithms are reliable, and the enable the MAV to identify landscapes and map them. DA - 2015-01 DB - ResearchSpace DP - CSIR KW - Miniature Aerial Vehicles KW - MAVs KW - Landscape mapping KW - Vanishing point KW - Vision algorithm KW - Hough transforms KW - Miniature aerial vehicle KW - Canny edge detector KW - Perspective cue KW - Graph SLAM LK - https://researchspace.csir.co.za PY - 2015 T1 - Landscape mapping MAV using single image perspective cues TI - Landscape mapping MAV using single image perspective cues UR - http://hdl.handle.net/10204/8144 ER - en_ZA


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