title: Dynamic programming and graph algorithms in computer vision.
abstract: Optimization is a powerful paradigm for expressing and solving problems in a wide range of areas, and has been successfully applied to many vision problems. Discrete optimization techniques are especially interesting since, by carefully exploiting problem structure, they often provide nontrivial guarantees concerning solution quality. In this paper, we review dynamic programming and graph algorithms, and discuss representative examples of how these discrete optimization techniques have been applied to some classical vision problems. We focus on the low-level vision problem of stereo, the mid-level problem of interactive object segmentation, and the high-level problem of model-based recognition.
authors.affiliation: Department of Computer Science, University of Chicago, 1100 E. 58th St., Chicago, IL 60637, USA. pff@cs.uchicago.edu
authors.forename: Pedro F
authors.initials: PF
authors.lastname: Felzenszwalb
authors.forename: Ramin
authors.initials: R
authors.lastname: Zabih
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D007089:Image Enhancement / Q000379:methods; D007091:Image Processing, Computer-Assisted / Q000379:methods; D014785:Vision, Ocular / Q000502:physiology*