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Screened Poisson Hyperfields for Shape Coding
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Date
2014-01-01
Author
Guler, R. A.
Tarı, Zehra Sibel
ÜNAL, GÖZDE
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We present a novel perspective on shape characterization using the screened Poisson equation. We discuss that the effect of the screening parameter is a change of measure of the underlying metric space. Screening also indicates a conditioned random walker biased by the choice of measure. A continuum of shape fields is created by varying the screening parameter or, equivalently, the bias of the random walker. In addition to creating a regional encoding of the diffusion with a different bias, we further break down the influence of boundary interactions by considering a number of independent random walks, each emanating from a certain boundary point, whose superposition yields the screened Poisson field. Probing the screened Poisson equation from these two complementary perspectives leads to a high-dimensional hyperfield: a rich characterization of the shape that encodes global, local, interior, and boundary interactions. To extract particular shape information as needed in a compact way from the hyperfield, we apply various decompositions either to unveil parts of a shape or parts of a boundary or to create consistent mappings. The latter technique involves lower-dimensional embeddings, which we call screened Poisson encoding maps (SPEM). The expressive power of the SPEM is demonstrated via illustrative experiments as well as a quantitative shape retrieval experiment over a public benchmark database on which the SPEM method shows a high-ranking performance among the existing state-of-the-art shape retrieval methods.
Subject Keywords
Screened Poisson equation
,
Elliptic models for distance transforms
,
Conditioned random walker
,
Shape decomposition
,
Screened Poisson encoding maps (SPEM)
,
Nonnegative sparse coding
,
Nonrigid shape retrieval
,
Level-set models
URI
https://hdl.handle.net/11511/32694
Journal
SIAM JOURNAL ON IMAGING SCIENCES
DOI
https://doi.org/10.1137/140956117
Collections
Department of Computer Engineering, Article
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R. A. Guler, Z. S. Tarı, and G. ÜNAL, “Screened Poisson Hyperfields for Shape Coding,”
SIAM JOURNAL ON IMAGING SCIENCES
, pp. 2558–2590, 2014, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/32694.