Camera Geometries for Image Matching in 3-D Machine Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Trinocular Stereo Vision for Robotics
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part II
Orientation Contrast Detection in Space-Variant Images
BMVC '00 Proceedings of the First IEEE International Workshop on Biologically Motivated Computer Vision
ICIP '95 Proceedings of the 1995 International Conference on Image Processing (Vol.2)-Volume 2 - Volume 2
Real Aperture Axial Stereo: Solving for Correspondences in Blur
Proceedings of the 31st DAGM Symposium on Pattern Recognition
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Stereo information can be obtained using a moving camera. If a dynamic scene is acquired using a translating camera and the camera motion parameters are known, then the analysis of the scene may be facilitated by ego-motion complex logarithmic mapping (ECLM). It is shown in this paper that by using the complex logarithmic mapping (CLM) with respect to the focus of expansion, the depth of stationary components can be determined easily in the transformed image sequence. The proposed approach for depth recovery avoids the difficult problems of establishing correspondence and computation of optical flow, by using the ego-motion information. An added advantage of the CLM will be the invariances it offers. We report our experiments with synthetic data to show the sensitivity of the depth recovery, and show results of real scenes to demonstrate the efficacy of the proposed motion stereo in applications such as autonomous navigation.