2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06) (2006)
New York, NY
June 17, 2006 to June 22, 2006
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CVPR.2006.224
Jingdong Wang , HKUST, Hong Kong
Long Quan , HKUST, Hong Kong
Jian Sun , Microsoft Research Asia, Beijing, China
Xiaoou Tang , Microsoft Research Asia, Beijing, China
Heung-Yeung Shum , Microsoft Research Asia, Beijing, China
In this paper, we address a novel problem of automatically creating a picture collage from a group of images. Picture collage is a kind of visual image summary - to arrange all input images on a given canvas, allowing overlay, to maximize visible visual information. We formulate the picture collage creation problem in a Bayesian framework. The salient regions of each image are firstly extracted and represented as a set of weighted rectangles. Then, the image arrangement is formulated as a Maximum a Posterior (MAP) problem such that the output picture collage shows as many visible salient regions (without being overlaid by others) from all images as possible. Moreover, a very efficientMarkov chain Monte Carlo (MCMC) method is designed for the optimization. Applications to desktop image browsing and image search result summarization demonstrate the effectiveness of our approach.
J. Wang, X. Tang, H. Shum, J. Sun and L. Quan, "Picture Collage," 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06)(CVPR), New York, NY, 2006, pp. 347-354.