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Real-time Quadrifocal Visual Odometry
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AI
DOI：10.1177/0278364909356601.png)
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In this paper we describe a new image-based approach to tracking the six-degree-of-freedom trajectory of a stereo camera pair. The proposed technique estimates the pose and subsequently the dense pixel matching between temporal image pairs in a sequence by performing dense spatial matching between images of a stereo reference pair. In this way a minimization approach is employed which directly uses all grayscale information available within the stereo pair (or stereo region) leading to very robust and precise results. Metric 3D structure constraints are imposed by consistently warping corresponding stereo images to generate novel viewpoints at each stereo acquisition. An iterative non-linear trajectory estimation approach is formulated based on a quadrifocal relationship between the image intensities within adjacent views of the stereo pair. A robust M-estimation technique is used to reject outliers corresponding to moving objects within the scene or other outliers such as occlusions and illumination changes. The technique is applied to recovering the trajectory of a moving vehicle in long and difficult sequences of images.
Keyword:
visual odometry
direct
dense 3D tracking stereo
multi-view geometry
期刊
IF:
5
论文数:
2.4K
被引数:
1.5W
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