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Abstract:
This work presents camera-based methods for dense scene reconstruction. In the context of binocular stereo vision, we introduce a novel algorithm for the efficient computation of dense disparity maps and a precise stereo method that is based on simulated random walks. Further, we present a novel method for the robust and efficient reconstruction from multiple views using a probabilistic formulation. In practice, we use these methods to realize various automotive parking assistance functionalities including an automatic parking slot detection, a collision detector for the pivoting ranges of the doors, and novel image based rendering techniques for visualization. The influence of reconstruction quality on application reliability is showcased with extensive experiments.
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Title: | Contributions to Stereo Vision |
Date: | 17 June 2013 |
Location: | 02.13.010 |
Abstract: | This work presents camera-based methods for dense scene reconstruction. In the context of binocular stereo vision, we introduce a novel algorithm for the efficient computation of dense disparity maps and a precise stereo method that is based on simulated random walks. Further,... |
Imageurl: | ![]() |
Type: | News |
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