Earticle

초록

영어

This paper presents a general framework for seamlessly combining multiple low cost and inaccurate estimated segmentation maps (with an arbitrary number of regions) of the same scene to achieve a final improved segmentation. The proposed fusion model is derived from the well-known precision-recall criterion, specially dedicated to the specific clustering problem of any spatially indexed data and which is also efficient and widely used in the vision community for evaluating both a region-based segmentation and the quality of contours produced by this segmentation map compared to one or multiple ground-truth segmentations of the same image. The proposed combination framework is here specifically designed to be robust with respect to outlier segmentations (that appear to be inconsistent with the remainder of the segmentation ensemble) and includes an explicit internal regularization factor reflecting the inherent ill-posed nature of the segmentation problem. We propose also a hierarchical and efficient way to optimize the consensus energy function related to this fusion model that exploits a simple and deterministic iterative relaxation strategy combining the different segments or individual regions belonging to the segmentation ensemble in the final solution. The experimental results on the Berkeley database with manual ground truth segmentations show the effectiveness of our combination model.

목차

Abstract
 1. Introduction
 2. Proposed Fusion Model
  2.1. The F Measure
  2.2. Consensus Energy-Based Fusion Model
  2.3. Fusion Model Optimization
 3. Segmentation Ensemble Generation
 4. Experimental Results
  4.1. Setup and Initial Tests
  4.2. Performance Measures & Comparison With State-Of-The-Art Methods
  4.3. Discussion
  4.4. Algorithm
 5. Conclusion
 References

키워드

저자

• Max Mignotte [ Université de Montréal, Faculté des Arts et des Sciences, Montréal H3C 3J7 QC, Canada ]
• Charles Helou [ Département d’Informatique et de Recherche Opérationnelle (DIRO), ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605