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Contour Detection and Hierarchical Image Segmentation

Arbeláez, Pablo and Maire, Michael and Fowlkes, Charless and Malik, Jitendra (2011) Contour Detection and Hierarchical Image Segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 33 (5). pp. 898-916. ISSN 0162-8828.

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This paper investigates two fundamental problems in computer vision: contour detection and image segmentation. We present state-of-the-art algorithms for both of these tasks. Our contour detector combines multiple local cues into a globalization framework based on spectral clustering. Our segmentation algorithm consists of generic machinery for transforming the output of any contour detector into a hierarchical region tree. In this manner, we reduce the problem of image segmentation to that of contour detection. Extensive experimental evaluation demonstrates that both our contour detection and segmentation methods significantly outperform competing algorithms. The automatically generated hierarchical segmentations can be interactively refined by userspecified annotations. Computation at multiple image resolutions provides a means of coupling our system to recognition applications.

Item Type:Article
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Fowlkes, Charless0000-0002-2990-1780
Additional Information:© 2011 IEEE. Manuscript received 16 Feb. 2010; accepted 5 July 2010; published online 19 Aug. 2010. Date of Current Version: 22 March 2011. Recommended for acceptance by P. Felzenszwalb.
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INSPEC Accession Number11874884
Issue or Number:5
Record Number:CaltechAUTHORS:20110415-113118411
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Official Citation:Arbeláez, P.; Maire, M.; Fowlkes, C.; Malik, J.; , "Contour Detection and Hierarchical Image Segmentation," Pattern Analysis and Machine Intelligence, IEEE Transactions on , vol.33, no.5, pp.898-916, May 2011 doi: 10.1109/TPAMI.2010.161 URL:
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:23346
Deposited By: Tony Diaz
Deposited On:19 Apr 2011 16:12
Last Modified:09 Mar 2020 13:18

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