Volumetric Semantic Segmentation using Pyramid Context Features.
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ABSTRACT:
SUBMITTER: Barron JT
PROVIDER: S-EPMC4445881 | biostudies-literature | 2013 Dec
REPOSITORIES: biostudies-literature
Publications
Volumetric Semantic Segmentation using Pyramid Context Features.
Barron Jonathan T JT Arbeláez Pablo P Keränen Soile V E SV Biggin Mark D MD Knowles David W DW Malik Jitendra J
Proceedings. IEEE International Conference on Computer Vision 20131201
We present an algorithm for the per-voxel semantic segmentation of a three-dimensional volume. At the core of our algorithm is a novel "pyramid context" feature, a descriptive representation designed such that exact per-voxel linear classification can be made extremely efficient. This feature not only allows for efficient semantic segmentation but enables other aspects of our algorithm, such as novel learned features and a stacked architecture that can reason about self-consistency. We demonstra ...[more]
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