Shape, Contour and Grouping in Computer Vision

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Forsyth, David A. (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Mundy, Joseph L. (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Gesu, Vito di (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Cipolla, Roberto (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 1999.
• Έκδοση: 1st ed. 1999.
• Σειρά: Lecture Notes in Computer Science, 1681
• Θέματα: Optical data processing.; Pattern recognition.; Computer graphics.; Artificial intelligence.; Image Processing and Computer Vision.; Pattern Recognition.; Computer Graphics.; Artificial Intelligence.

Computer vision has been successful in several important applications recently. Vision techniques can now be used to build very good models of buildings from pictures quickly and easily, to overlay operation planning data on a neuros- geon's view of a patient, and to recognise some of the gestu...

Πίνακας περιεχομένων:

• An Empirical-Statistical Agenda for Recognition
• A Formal-Physical Agenda for Recognition
• Shape
• Shape Models and Object Recognition
• Order Structure, Correspondence, and Shape Based Categories
• Quasi-Invariant Parameterisations and Their Applications in Computer Vision
• Shading
• Representations for Recognition Under Variable Illumination
• Shadows, Shading, and Projective Ambiguity
• Grouping
• Grouping in the Normalized Cut Framework
• Geometric Grouping of Repeated Elements within Images
• Constrained Symmetry for Change Detection
• Grouping Based on Coupled Diffusion Maps
• Representation and Recognition
• Integrating Geometric and Photometric Information for Image Retrieval
• Towards the Integration of Geometric and Appearance-Based Object Recognition
• Recognizing Objects Using Color-Annotated Adjacency Graphs
• A Cooperating Strategy for Objects Recognition
• Statistics, Learning and Recognition
• Model Selection for Two View Geometry:A Review
• Finding Objects by Grouping Primitives
• Object Recognition with Gradient-Based Learning.