Picture Collage

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 conditional random field model, which integrates image salience, canvas constraint, natural preference, and user interaction. Each image is represented by a group of weighted rectangles, which indicate the salient regions. Then picture collage is resolved by minimizing the energy, guided by the constraints. A two-step optimization method is proposed. First, a quick initialization algorithm based on the proposed 1D collage method is presented. Second, a very efficient Markov chain Monte Carlo method is designed for the refined optimization. We also integrate user interaction in the formulation and optimization to obtain an interactive collage reflecting personalized preference. Visual and quantitative experimental evaluations indicate the efficiency of the proposed collage creation technique.

[1]  Clayton Brian Atkins Adaptive photo collection page layout , 2004, 2004 International Conference on Image Processing, 2004. ICIP '04..

[2]  Alexander C. Loui,et al.  Using Genetic Algorithms for Album Page Layouts , 2003, IEEE Multim..

[3]  Yoji Kajitani,et al.  Rectangle-packing-based module placement , 1995, ICCAD.

[4]  Victor J. Milenkovic,et al.  Rotational polygon containment and minimum enclosure using only robust 2D constructions , 1999, Comput. Geom..

[5]  Tim Hesterberg,et al.  Monte Carlo Strategies in Scientific Computing , 2002, Technometrics.

[6]  David Salesin,et al.  Interactive digital photomontage , 2004, ACM Trans. Graph..

[7]  Jun S. Liu,et al.  Multipoint metropolis method with application to hybrid Monte Carlo , 2001 .

[8]  Brendan J. Frey,et al.  Epitomic analysis of appearance and shape , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

[9]  Jitendra Malik,et al.  Blobworld: Image Segmentation Using Expectation-Maximization and Its Application to Image Querying , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[10]  Pietro Perona,et al.  A Bayesian approach to unsupervised one-shot learning of object categories , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.