A Guided Tour of Computer VisionAn introduction to computer vision, covering the structure and properties of the visual world. This concise guide stresses fundamental concepts, and also provides details and pointers with respect to recent developments. The author pursues the narrow view of vision covering the structure and properties of the visual world, thereby providing a lucid introduction for the novice and a fresh perspective to the expert. |
Contents
Introduction 3 | 3 |
Image Formation | 31 |
Edge Detection and Image Segmentation | 75 |
Copyright | |
7 other sections not shown
Common terms and phrases
Analysis and Machine angle aperture approach Artificial Intelligence assume assumption axis Binford camera center of projection Computer Vision constraint correspondence curvature curve depth discontinuities derivatives digital image direction domain Doorn edge detection edgel Fourier function Gauss map Gaussian curvature Gaussian image Gaussian sphere gradient space Huffman IEEE IEEE Transactions Ikeuchi illumination illustrated in Figure image intensity image irradiance image plane image point Image Processing image segmentation image textural image velocity imaged surface instance isobrightness contours Kanade Koenderink labels lens line drawing linear Machine Intelligence matching Möbius strip motion field motion-field estimation Nalwa noise object point occluding operator optical orthogonal orthographic projection parabolic parameters Pattern Analysis perspective projection pixels position provides quantization reflectance map representation retina rotation sampling scale scene point Section shape step edge straight line superellipse surface normal surface patch surface-normal orientation tangent texels three-dimensional Transactions on Pattern transform translation two-dimensional variation vector viewpoint visual