OSA's Digital Library

Virtual Journal for Biomedical Optics

Virtual Journal for Biomedical Optics

| EXPLORING THE INTERFACE OF LIGHT AND BIOMEDICINE

  • Editor: Gregory W. Faris
  • Vol. 1, Iss. 11 — Nov. 13, 2006

Object-of-interest image segmentation based on human attention and semantic region clustering

Byoung Chul Ko and Jae-Yeal Nam  »View Author Affiliations


JOSA A, Vol. 23, Issue 10, pp. 2462-2470 (2006)
http://dx.doi.org/10.1364/JOSAA.23.002462


View Full Text Article

Acrobat PDF (1074 KB)





Browse Journals / Lookup Meetings

Browse by Journal and Year


   


Lookup Conference Papers

Close Browse Journals / Lookup Meetings

Article Tools

Share
Citations

Abstract

We propose a novel object-of-interest (OOI) segmentation algorithm for various images that is based on human attention and semantic region clustering. As object-based image segmentation is beyond current computer vision techniques, the proposed method segments an image into regions, which are then merged as a semantic object. At the same time, an attention window (AW) is created based on the saliency map and saliency points from an image. Within the AW, a support vector machine is used to select the salient regions, which are then clustered into the OOI using the proposed region merging. Unlike other algorithms, the proposed method allows multiple OOIs to be segmented according to the saliency map.

© 2006 Optical Society of America

OCIS Codes
(100.2960) Image processing : Image analysis
(100.5010) Image processing : Pattern recognition
(110.2960) Imaging systems : Image analysis
(330.1800) Vision, color, and visual optics : Vision - contrast sensitivity
(330.1880) Vision, color, and visual optics : Detection

ToC Category:
Image Processing

History
Original Manuscript: January 6, 2006
Revised Manuscript: March 22, 2006
Manuscript Accepted: April 26, 2006

Virtual Issues
Vol. 1, Iss. 11 Virtual Journal for Biomedical Optics

Citation
Byoung Chul Ko and Jae-Yeal Nam, "Object-of-interest image segmentation based on human attention and semantic region clustering," J. Opt. Soc. Am. A 23, 2462-2470 (2006)
http://www.opticsinfobase.org/vjbo/abstract.cfm?URI=josaa-23-10-2462


Sort:  Author  |  Year  |  Journal  |  Reset

References

  1. Q. Tian, Y. Wu, and T. S. Huang, "Combine user defined region-of-interest and spatial layout for image retrieval," in Proceedings of the 2000 IEEE International Conference on Image Processing (IEEE Press, 2000), pp. 746-749.
  2. S. Kim, S. Park, and M. Kim, "Central object extraction for object-based image retrieval," in Proceedings of the International Conference on Image and Video Retrieval (Association for Computing Machinery, 2003), pp. 39-49.
  3. W. Wang, Y. Song, and A. Zhang, "Semantics retrieval by region saliency," in Proceedings of the International Conference on Image and Video Retrieval (Association for Computing Machinery, 2002), pp. 29-37.
  4. W. Osberger and A. J. Naeder, "Automatic identification of perceptually important regions in an image," in Proceedings of the IEEE International Conference on Pattern Recognition (IEEE Press, 1998), pp. 701-704.
  5. Y.-F. Ma and H.-J. Zhang, "Content-based image attention analysis by using fuzzy growing," in Proceedings of the International Conference on ACM Multimedia (Association for Computing Machinery, 2003), pp. 374-381.
  6. J. Z. Wang, J. Li, R. M. Gray, and G. Wiederhold, "Unsupervised multiresolution segmentation for images with low depth of field," IEEE Trans. Pattern Anal. Mach. Intell. 23, 85-90 (2001).
  7. C. Kim, "Segmenting a low-depth-of-field image using morphological filters and region merging," IEEE Trans. Image Process. 14, 1503-1511 (2005).
  8. B. Suh, H. Ling, B. Bederson, and D. W. Jacob, "Automatic thumbnail cropping and its effectiveness," in Proceedings of the 16th ACM Symposium on User Interface Software and Technology (Association of Computer Machinery, 2003), pp. 95-104.
  9. G. Lei and G. B. Long, "A watermarking scheme using image object region," in Proceedings of the IEEE International Conference on Computational Intelligence and Multimedia Applications (IEEE Press, 2003), pp. 419-423.
  10. B. C. Ko and H. Byun, "Frip: a region-based image retrieval tool using automatic image segmentation and stepwise boolean and matching," IEEE Trans. Multimedia 7, 105-113 (2005).
  11. J. M. Wolfe, "Guided search 2.0: a revised model of visual search," Psychon. Bull. Rev. 1, 202-238 (1994).
  12. L. Itti, C. Koch, and E. Niebur, "A model of saliency-based visual attention for rapid scene analysis," IEEE Trans. Pattern Anal. Mach. Intell. 20, 1254-1259 (1998).
  13. E. Loupias and N. Sebe, "Wavelet-based salient points for image retrieval," Research Report RR 99.11 (RFV-INSA Lyon, 1999).
  14. B. Moghaddam and M.-H. Yang, "Gender classification with support vector machines," in Proceedings of the IEEE International Conference on Automatic Face and Gesture Recognition (IEEE Press, 2000), pp. 306-311.
  15. L. Fei-Fei, R. Fergus, and P. Perona, "Learning generative visual models from few training examples: an incremental Bayesian approach tested on 101 object categories," CVPR 2004, Workshop on Generative-Model Based Vision (IEEE, 2004).
  16. C. Yimand and A. C. Bovik, "Multiresolution 3-D range segmentation using focused cues," IEEE Trans. Image Process. 7, 1283-1299 (1998).
  17. Z. Ye and C. C. Lu, "Unsupervised multiscale focused objects detection using hidden Markov tree," in Proceedings of the International Conference on Computer Vision, Pattern Recognition, and Image Processing (IEEE Press, 2002), pp. 812-815.
  18. The OOI segmentation results can be found at http:/video.kmu.ac.kr/cvpr/OOI-results/OOIResults.htm

Cited By

Alert me when this paper is cited

OSA is able to provide readers links to articles that cite this paper by participating in CrossRef's Cited-By Linking service. CrossRef includes content from more than 3000 publishers and societies. In addition to listing OSA journal articles that cite this paper, citing articles from other participating publishers will also be listed.


« Previous Article  |  Next Article »

OSA is a member of CrossRef.

CrossCheck Deposited