2026-05-30T11:01:31Zhttps://riuma.uma.es/rest/oai/requestoai:riuma.uma.es:10630/151272026-02-03T12:16:04Zcom_10630_2254col_10630_37959
RIUMA. Repositorio Institucional de la Universidad de Málaga
author
Gómez-Ojeda, Rubén
author
González-Jiménez, Antonio Javier
2018-02-07T08:18:18Z
2018-02-07T08:18:18Z
2018-02-07
https://hdl.handle.net/10630/15127
Most approaches to stereo visual odometry reconstruct the motion based on the tracking of point features along a sequence of images. However, in low-textured scenes it is often difficult to encounter a large set of point features, or it may happen that they are not well distributed over the image, so that the behavior of these algorithms deteriorates. This paper proposes a probabilistic approach to stereo visual odometry based on the combination of both point and line segment that works robustly in a wide variety of scenarios. The camera motion is recovered through non-linear minimization of the projection errors of both point and line segment features. The method, of course, is computationally more expensive that using only one type of feature, but still can run in real-time on a standard computer and provides interesting advantages, including a straightforward integration into any probabilistic framework commonly employed in mobile robotics.
eng
Attribution-NonCommercial-NoDerivatives 4.0 Internacional
Robótica
Stereo visual odometry by combining points and lines
conference output
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URL
https://riuma.uma.es/bitstreams/8ff2ec39-1bb7-4d8e-a93f-cf6ab95ea53a/download
File
MD5
30103b4d3bcf54b1f97ad100b699954e
1832397
application/pdf
icvss-poster.pdf