Projective Alignment with Regions

?We have recently proposed an approach to recognition that uses regions to determine the pose of objects while allowing for partial occlusion of the regions. Regions introduce an attractive alternative to existing global and local approaches, since, unlike global features, they can handle occlusion and segmentation errors, and unlike local features they are not as sensitive to sensor errors, and they are easier to match. The region-based approach also uses image information directly, without the construction of intermediate representations, such as algebraic descriptions, which may be difficult to reliably compute. In this paper, we further analyze properties of the method for planar objects undergoing projective transformations. In particular, we prove that three visible regions are sufficient to determine the transformation uniquely and that for a large class of objects, two regions are insufficient for this purpose. However, we show that when several regions are available, the pose ...

• Type: Conference
• Year: 1999
• Where: ICCV
• Authors: Ronen Basri, David W. Jacobs
• Keywords: Computer Vision, ICCV 1999, Partial Occlusion, Planar Objects, Projective Transformations, Segmentation Errors, Visible Regions