Computer and Robot Vision, Volume 2This two-volume set is an authoritative, comprehensive, modern work on computer vision that covers all of the different areas of vision with a balance and unified approach. Volume II covers the higher level techniques of illumination, perspective projection, analytical photogrammetry, motion, image matching, consistent labeling, model matching, and knowledge based vision systems.Both volumes of Computer and Robot Vision address the growing and rapidly evolving area of computer vision with depth and breadth and explore details and specific algorithms not available in most competing texts. |
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3D point algorithm Analysis and Machine angle assume b₁ b₂ collinear components Computer Vision constraint corresponding cross-ratio defined depth error derived determined edge equation estimation function ƒ² Gaussian given Haralick homomorphism IEEE IEEE Transactions image plane image points Image Processing intersection iteration label least-squares lens line segment linear Machine Intelligence mapping matching measure MF-estimator N-tuple node nonlinear normal object observed obtain optic flow outliers P₁ pair parameters Pattern Analysis Pattern Recognition perspective projection Photogrammetry pixel planar polarized position problem procedure projection plane reference frame relation represent rigid motion rigid-motion Robot robust rotation matrix sequence shape SNR(db solution solve spatial stereo structure Suppose surface normal surface patch techniques three-dimensional Transactions on Pattern transformation translational tree search two-dimensional u₁ unknown variance vector velocity error