Computer Vision From Surfaces to 3D Objects
The typical computational approach to object understanding derives shape information from the 2D outline of the objects. For complex object structures, however, such a planar approach cannot determine object shape; the structural edges have to be encoded in terms of their full 3D spatial configuration. Computer Vision: From Surfaces to 3D Objects is the first book to take a full approach to the challenging issue of veridical 3D object representation. It introduces mathematical and conceptual advances that offer an unprecedented framework for analyzing the complex scene structure of the world.
An Unprecedented Framework for Complex Object Representation
Presenting the material from both computational and neural implementation perspectives, the book covers novel analytic techniques for all levels of the surface representation problem. The cutting-edge contributions in this work run the gamut from the basic issue of the ground plane for surface estimation through mid-level analyses of surface segmentation processes to complex Riemannian space methods for representing and evaluating surfaces.
State-of-the-Art 3D Surface and Object Representation
This well-illustrated book takes a fresh look at the issue of 3D object representation. It provides a comprehensive survey of current approaches to the computational reconstruction of surface structure in the visual scene.
Introduction. Scene Statistics and 3D Surface Perception. The Theory of Swirling Fields: Segmenting a Scene into Surfaces. Mechanisms for Propagating Surface Information in 3D Reconstruction. 3D Surface Representation Using Ricci Flow. Cue Interpretation and Propagation: Flat versus Nonflat Visual Surfaces. Symmetry, Shape, Surfaces, and Objects. Noncommutative Field Theory in the Primary Visual Cortex. Contour-, Surface-, and Object-Related Coding in the Visual Cortex. From Surfaces to Objects: A Neuroanalytic Approach. 3D and Spatiotemporal Interpolation in Object and Surface Formation. The Perceptual Representation of 3D Shape. References. Index.