We present a unified Bayesian approach to shape representation and related problems in perceptual organization, including part decomposition, shape similarity, figure/ground estimation, and 3D shape. The approach is based on the idea of estimating the skeletal structure most likely to have generated the observed shape via a process of stochastic “growth.” We survey the approach briefly and show how it can be extended in a principled way to solve a wide array of related problems.
CITATION STYLE
Feldman, J., Singh, M., Briscoe, E., Froyen, V., Kim, S., & Wilder, J. (2013). An Integrated Bayesian Approach to Shape Representation and Perceptual Organization (pp. 55–70). https://doi.org/10.1007/978-1-4471-5195-1_4
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