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Grouping with Bias
S. Yu and J. Shi
tech. report CMU-RI-TR-01-22, Robotics Institute, Carnegie Mellon University, July, 2001.

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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.

Sponsor: DARPA
Grant ID: ONR N00014-00-1-0915 and NSF IRI-9817496

S. Yu and J. Shi, Grouping with Bias, tech. report CMU-RI-TR-01-22, Robotics Institute, Carnegie Mellon University, July, 2001.

@techreport{Yu_2001_3765,
   author = "Stella Yu and Jianbo Shi",
   title = "Grouping with Bias",
   institution = "Robotics Institute, Carnegie Mellon University",
   month = "July",
   year = "2001",
   number = "CMU-RI-TR-01-22",
   address = "Pittsburgh, PA"
}