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IJCAI
2007

Depth Estimation Using Monocular and Stereo Cues

8 years 11 months ago
Depth Estimation Using Monocular and Stereo Cues
Depth estimation in computer vision and robotics is most commonly done via stereo vision (stereopsis), in which images from two cameras are used to triangulate and estimate distances. However, there are also numerous monocular visual cues— such as texture variations and gradients, defocus, color/haze, etc.—that have heretofore been little exploited in such systems. Some of these cues apply even in regions without texture, where stereo would work poorly. In this paper, we apply a Markov Random Field (MRF) learning algorithm to capture some of these monocular cues, and incorporate them into a stereo system. We show that by adding monocular cues to stereo (triangulation) ones, we obtain significantly more accurate depth estimates than is possible using either monocular or stereo cues alone. This holds true for a large variety of environments, including both indoor environments and unstructured outdoor environments containing trees/forests, buildings, etc. Our approach is general, an...
Ashutosh Saxena, Jamie Schulte, Andrew Y. Ng
Added 29 Oct 2010
Updated 29 Oct 2010
Type Conference
Year 2007
Where IJCAI
Authors Ashutosh Saxena, Jamie Schulte, Andrew Y. Ng
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