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Computing Depth Maps From Descent Imagery
Yalin Xiong, Clark F. Olson, and Larry H. Matthies In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, volume 1, pages 392-397, 2001. Download (331 K) In the exploration of the other planets of our solar system, images taken during a lander's descent to the surface of a planet provide a critical link between orbital images and surface images. The descent images not only allow us to locate the landing site in a global coordinate frame, but also provide progressively higher-resolution maps for mission planning. This paper addresses the generation of depth maps from the descent images. Our approach has two steps, motion refinement and depth recovery. During motion refinement, we use an initial motion estimate in order to avoid the intrinsic ambiguity in descending motions. The objective of the motion refinement step is to adjust the motion parameters such that the epipolar constraints are valid between adjacent frames. The depth recovery step correlates adjacent frames to match pixels for triangulation. Due to the descending motion, the conventional rectification process is replaced by a set of anti-aliasing image warpings corresponding to a set of virtual parallel planes. We demonstrate experimental results on synthetic and real descent images. |
