Resolving Empty Patches in Vision-based Scene Reconstructions
Autor: | Georges Younes, Imad H. Elhajj, Daniel Asmar, Joseph Nasr |
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Rok vydání: | 2020 |
Předmět: |
0209 industrial biotechnology
Vision based Computer science business.industry Perspective (graphical) ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 02 engineering and technology Texture (music) 020901 industrial engineering & automation Planar 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Computer vision Motion planning Artificial intelligence business ComputingMethodologies_COMPUTERGRAPHICS |
Zdroj: | SMC |
DOI: | 10.1109/smc42975.2020.9283303 |
Popis: | Whether for localization, path planning, or scene manipulation, complete and accurate scene reconstruction is an essential component of robotic operation. Due to their low cost and versatility, vision-based scene reconstruction methods have been the subject of research for decades. However, a major disadvantage of vision-based methods is that they require the scene to be populated with distinctive features that can be unambiguously matched across different images. In the absence of these features, such as in planar homogeneously painted surfaces, the scene reconstruction fails. This paper proposes a novel idea, where the user can virtually texturize planar surfaces at run-time to be used for the scene reconstruction. To do so, the corners of planes are tracked across the images and used to warp virtual texture patches to the correct perspective. Two methods are then proposed, one that actively tracks the corners as long as they are in view, and one that requires the camera poses to augment planes once their corners are no longer visible. The conducted experiments demonstrate the effectiveness of our approach as it increases the number of points in scene reconstructions. The end result is a denser scene reconstruction where textureless planes, typically not recovered in traditional methods, are reconstructed. |
Databáze: | OpenAIRE |
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