Fast Stereo Matching Using Rectangular Subregioning and 3D Maximum-Surface Techniques
International Journal of Computer Vision
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
Lucas-Kanade 20 Years On: A Unifying Framework
International Journal of Computer Vision
Sampling the Disparity Space Image
IEEE Transactions on Pattern Analysis and Machine Intelligence
CVPRW '04 Proceedings of the 2004 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'04) Volume 12 - Volume 12
Improved Sub-pixel Stereo Correspondences through Symmetric Refinement
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Speeded-Up Robust Features (SURF)
Computer Vision and Image Understanding
A Bayesian formulation for sub-pixel refinement in stereo orbital imagery
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Robust mosaicking of stereo digital elevation models from the ames stereo pipeline
ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part II
Outlier removal in stereo reconstruction of orbital images
ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part III
Orthographic stereo correlator on the terrain model for Apollo metric images
ISVC'11 Proceedings of the 7th international conference on Advances in visual computing - Volume Part I
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Generating accurate three dimensional planetary models is becoming increasingly important as NASA plans manned missions to return to the Moon in the next decade. This paper describes a 3D surface reconstruction system called the Ames Stereo Pipeline that is designed to produce such models automatically by processing orbital stereo imagery. We discuss two important core aspects of this system: (1) refinement of satellite station positions and pose estimates through least squares bundle adjustment; and (2) a stochastic plane fitting algorithm that generalizes the Lucas-Kanade method for optimal matching between stereo pair images.. These techniques allow us to automatically produce seamless, highly accurate digital elevation models from multiple stereo image pairs while significantly reducing the influence of image noise. Our technique is demonstrated on a set of 71 high resolution scanned images from the Apollo 15 mission.