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Grouping with Bias
- Stella X. YU and Jianbo SHI
Technical report CMU-RI-TR-01-22, Robotics Institute, Carnegie Mellon University, 2001.
- Abstract
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We present a graph partitioning method to integrate prior knowledge
in data grouping. We consider priors represented by three types of
constraints: unitary constraints on labelling of groups, partial
a priori grouping information, external influence on binary
constraints. They are modelled as biases in the grouping process.
We incorporate these biases into graph partitioning criteria.
Computationally this formulation leads to a constrained
eigenproblem. We demonstrate the effectiveness of this algorithm on
image segmentation with priors and object detection with spatial
attention.
- Keywords
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image segmentation, figure-ground, grouping, graph partitioning, bias, spatial attention
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