DocumentCode
1878256
Title
Object discovery with perceptual grouping
Author
Liu, David ; Chen, Tsuhan
Author_Institution
Dept. of Electr. & Comput. Eng., Carnegie Mellon Univ., Pittsburgh, PA
fYear
2008
fDate
12-15 Oct. 2008
Firstpage
3032
Lastpage
3035
Abstract
We propose an iterative method for discovering objects in images. In each iteration, the current estimate of the layout is processed by a sequence of perceptual grouping rules. Perceptual grouping appears to be the basis of visual organization of human. It is concerned with the problem of the formation of wholes from parts. The method does not rely on the mixture of Gaussian model and hence avoids the model selection problem. We use synthetic and real images to demonstrate that the obtained result is better than that obtained by other methods.
Keywords
image processing; iterative methods; human perception; image objects; perceptual grouping rules; posterior map; probabilistic model; spatial distribution; Bayesian methods; Data mining; Gaussian distribution; Humans; Image segmentation; Iterative methods; Layout; Low pass filters; Probability distribution; Unsupervised learning; EM algorithm; low pass filter; unsupervised learning;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Processing, 2008. ICIP 2008. 15th IEEE International Conference on
Conference_Location
San Diego, CA
ISSN
1522-4880
Print_ISBN
978-1-4244-1765-0
Electronic_ISBN
1522-4880
Type
conf
DOI
10.1109/ICIP.2008.4712434
Filename
4712434
Link To Document