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portada visual object class recognition using local descriptions
Type
Physical Book
Author
Publisher
Year
2009
Language
English
Pages
164
Format
Paperback
Dimensions
22.9 x 15.2 x 0.9 cm
Weight
0.23 kg.
ISBN
3838105788
ISBN13
9783838105789
Categories

visual object class recognition using local descriptions

Alexandra Teynor (Author) · Sudwestdeutscher Verlag Fur Hochschulschrifte · Paperback

visual object class recognition using local descriptions - Teynor, Alexandra

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R 1,563
R 1,563

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Synopsis "visual object class recognition using local descriptions"

Huge collections of digital images exist on the web, in large company databases or on our private hard disks. When the images have not been annotated by keywords, finding pictures containing certain objects is a difficult task. This work deals with the recognition of visual object class members in digital photographs, solely using the image data. The fundamental principle of all methods employed and developed in this thesis is the use of local, visual features. One focus is to find suitable prototype parts for modeling the object classes. Several issues like the suitability of interest point detectors, the fast generation of visual codebooks and the discrepancy between visual and semantic similarity of structures are discussed and advanced techniques are developed based on the findings. The second focus of this work is the modeling of the visual object classes using the local parts. In particular, methods that incorporate the geometric relationship of the local features have proven to be beneficial.

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