tailieunhanh - Active Visual Inference of Surface Shape - Roberto Cipolla Part 2

Tham khảo tài liệu 'active visual inference of surface shape - roberto cipolla part 2', kỹ thuật - công nghệ, cơ khí - chế tạo máy phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | 6 Chap. 1. Introduction line and arc primitives are apparent contours see below . These do not convey a curved surface s shape in the same way. Their contour generators move and deform over a curved object s surface as the viewpoint is changed. These can defeat many stereo and structure from motion algorithms since the features contours in different viewpoints are projections of different scene points. This is effectively introducing non-rigidity. Representation Many existing methods make explicit quantitative depths of visible points 90 7 96 . Surfaces are then reconstructed from these sparse data by interpolation or fitting surface models - the plane being a particularly common and useful example. For arbitrarily curved smooth surfaces however no surface model is available that is general enough. The absence of adequate surface models and the sparsity of surface features make describing and inferring geometric information about 3D curved objects from visual cues a challenging problem in computer vision. Developing theories and methods to recover reliable descriptions of arbitrarily curved smooth surfaces is one of the major themes of this thesis. 2. Robustness The lack of robustness of computer vision systems compared to biological systems has led many to question the suitability of existing computational theories 194 . Many existing methods are inadequate or incomplete and require development to make then robust and capable of recovering from error. Existing structure from motion algorithms have proved to be of little or no practical use when analysing images in which perspective effects are small. Their solutions are often ill-conditioned and fail in the presence of small quantities of image measurement noise when the field of view and the variation of depths in the scene is small or in the presence of small degrees of non-rigidity see Chapter 5 for details . Worst they often fail in particularly graceless fashions 197 60 . Yet the human visual system gains .