Title :
Object discovery with perceptual grouping
Author :
Liu, David ; Chen, Tsuhan
Author_Institution :
Dept. of Electr. & Comput. Eng., Carnegie Mellon Univ., Pittsburgh, PA
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;
Conference_Titel :
Image Processing, 2008. ICIP 2008. 15th IEEE International Conference on
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4244-1765-0
Electronic_ISBN :
1522-4880
DOI :
10.1109/ICIP.2008.4712434