Title :
A syntax for image understanding
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Illinois at Urbana-Champaign, Urbana, IL, USA
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;
Conference_Titel :
Computer Vision and Pattern Recognition Workshops, 2009. CVPR Workshops 2009. IEEE Computer Society Conference on
Conference_Location :
Miami, FL
Print_ISBN :
978-1-4244-3994-2
DOI :
10.1109/CVPRW.2009.5204337