DocumentCode :
2962612
Title :
A syntax for image understanding
Author :
Ahuja, Narendra
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Illinois at Urbana-Champaign, Urbana, IL, USA
fYear :
2009
fDate :
20-25 June 2009
Firstpage :
9
Lastpage :
10
Abstract :
We consider one of the most basic questions in computer vision, that of finding a low-level image representation that could be used to seed diverse, subsequent computations of image understanding. Can we define a relatively general purpose image representation which would serve as the syntax for diverse needs of image understanding? What makes good image syntax? How do we evaluate it? We pose a series of such questions and evolve a set of answers to them, which in turn help evolve an image representation. For concreteness, we first perform this exercise in the specific context of the following problem.
Keywords :
computer vision; image representation; computer vision; image understanding syntax; low-level image representation; seed diverse image understanding; Computer vision; Humans; Image representation; Image segmentation; Layout; Object oriented modeling; Photometry; Probability distribution; Taxonomy; Tree graphs;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition Workshops, 2009. CVPR Workshops 2009. IEEE Computer Society Conference on
Conference_Location :
Miami, FL
ISSN :
2160-7508
Print_ISBN :
978-1-4244-3994-2
Type :
conf
DOI :
10.1109/CVPRW.2009.5204337
Filename :
5204337
Link To Document :
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