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Incorporating shape into spatially-aware adaptive object segmentation algorithm

Published: 27 June 2012 Publication History

Abstract

Semantically accurate segmentation of a particular Object Of Interest (OOI) in an image is an important but challenging step in computer vision tasks. Our recently proposed object-specific segmentation algorithm learns a model of the OOI which includes information on both the visual appearance of and the spatial relationships among the OOI components. However, its performance heavily depends on the assumption that the visual appearance variability among OOI instances is low. We present an extension to our algorithm that relaxes this assumption by incorporating shape information into the OOI model. Experimental results and an ANOVA-based statistical test confirm that the incorporation of shape has a highly significant positive effect on segmentation performance.

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      C3S2E '12: Proceedings of the Fifth International C* Conference on Computer Science and Software Engineering
      June 2012
      139 pages
      ISBN:9781450310840
      DOI:10.1145/2347583
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      Published: 27 June 2012

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      Author Tags

      1. Bayesian network
      2. computer vision
      3. image segmentation
      4. multiple instance learning
      5. object recognition
      6. spatial relationship

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      • University of Limerick
      • Concordia University

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