Pages: p. 641
This issue contains the second installment of the special issue on perceptual organization in computer vision. In the April issue of TPAMI, we published 11 papers addressing basic principles, algorithms, and applications. This month's papers continue along these lines and raising new issues as well.
The first paper in the special section contributes to one of the most significant trends in perceptual organization, the use of graph algorithms to efficiently find regions that globally optimize, or approximately optimize, a grouping property. P. Soundararajan and S. Sarkar present an analysis and experimental evaluation of a set of graph algorithms, showing that some of the common algorithms are practically equivalent with respect to performance.
In the next paper, J.H. Elder, A. Krupnik, and L.A. Johnston describe a probabilistic formulation for contour grouping that combines Gestalt grouping cues with prior knowledge about the shape of the objects whose boundary is being detected. They apply this approach to the problem of detecting exact lake boundaries in satellite imagery.
S. Wang and J.M. Siskind also study graph algorithms as a grouping mechanism. They present a novel algorithm based on the ratio of two properties of graph edges that are cut in a segmentation. This leads to a polynomial time algorithm that finds globally optimal groupings, which they then enhance using a set of heuristics.
Finally, it is fitting that our issue concludes with S.-C. Zhu's paper, which reviews a large set of past work on modeling visual patterns, an area fundamental to perceptual organization. Professor Zhu presents a broad taxonomy of methods, stressing the importance of generative models in image modeling.
The 15 papers we have presented provide a wide range of viewpoints and attack a variety of problems using diverse tools. We find this appropriate since the challenges of perceptual organization are great and many angles on the problem should continue to be explored. Hopefully, the special section will provide a useful snapshot of the state of many of these approaches.
David W. Jacobs