By Yi Ma; et al
This ebook introduces the geometry of 3D imaginative and prescient, that's, the reconstruction of 3D versions of gadgets from a set of 2-D photos. It information the vintage conception of 2 view geometry and exhibits extra right device for learning the geometry of a number of perspectives is the so-called rank attention of the a number of view matrix. It additionally develops useful reconstruction algorithms and discusses attainable extensions of the theory.
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Extra info for An invitation to 3-D vision : from images to geometric models
Weinmann M, Dittrich A, Hinz S, Jutzi B (2013) Automatic feature-based point cloud registration for a moving sensor platform. Int Arch Photogramm Remote Sens Spat Inf Sci XL1/W1:373–378 16. Weinmann M, Jutzi B, Mallet C (2013) Feature relevance assessment for the semantic interpretation of 3D point cloud data. ISPRS Ann Photogramm Remote Sens Spat Inf Sci II-5/W2:313– 318 17. Weinmann M, Jutzi B, Mallet C (2014) Describing Paris: automated 3D scene analysis via distinctive low-level geometric features.
7 Raw 3D point cloud data, 3D point cloud data filtered via intensity information, 3D point cloud data filtered via the measure σr,3×3 of range reliability and 3D point cloud data filtered via the measure Pλ,3×3 of local planarity (from top to bottom) at the edges are considered as unreliable. This is due to the consideration of relatively small (3 × 3) image neighborhoods, where no significant deviation in range direction and no significant deviation from a locally planar surface may be observed.
For each measure, the corresponding effect in 3D space is visualized in Fig. 7. This figure clearly reveals that the use of intensity information alone is not sufficient to adequately filter raw 3D point cloud data and thereby completely remove the noisy behavior. In contrast, the strategies based on the two geometric measures retain adequate representations of local object surfaces. Whereas the strategy based on the measure σr,3×3 of range reliability provides almost planar object surfaces for significantly varying incidence angles (Fig.
An invitation to 3-D vision : from images to geometric models by Yi Ma; et al