Spatial Bayesian surprise for image saliency and quality assessment

Proceedings - International Conference on Image Processing, ICIP

Volumn , Issue , 2010, Pages 1081-1084

  Gkioulekas, Ioannis ^a   Evangelopoulos, Georgios ^b   Maragos, Petros ^b  

^a HARVARD UNIVERSITY   (United States)

^b NATIONAL TECHNICAL UNIVERSITY OF ATHENS   (Greece)

Author keywords

Bayesian surprise; Image quality assessment; Image saliency; Region detection; Visual attention

Indexed keywords

BAYESIAN; IMAGE QUALITY ASSESSMENT; IMAGE SALIENCY; REGION DETECTION; VISUAL ATTENTION;

BAYESIAN NETWORKS; IMAGE QUALITY; IMAGING SYSTEMS; RATING;

TRACKING (POSITION);

EID: 78651099227     PISSN: 15224880     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICIP.2010.5650991     Document Type: Conference Paper

References (15)

1. D. Walther and C. Koch, "Modeling attention to salient proto-objects," Neural Networks, vol. 19, no. 9, pp. 1395-1407, 2006.
2. A. Ninassi, O. Le Meur, P. Le Callet, and D. Barba, "Does where you gaze on an image affect your perception of quality? Applying visual attention to image quality metric," in ICIP, 2007.
3. Q. Ma and L. Zhang, "Saliency-based image quality assessment criterion," LNCS, vol. 5226, no. 1124-1133, pp. 1, 2008.
4. E.C. Larson, C. Vu, and D.M. Chandler, "Can visual fixation patterns improve image fidelity assessment?," in ICIP, 2008.
5. A.K. Moorthy and A.C. Bovik, "Visual importance pooling for image quality assessment," IEEE JSTSP, vol. 3, no. 2, pp. 193-201, 2009.
6. L. Itti and C. Koch, "A saliency-based search mechanism for overt and covert shifts of visual attention," Vision research, vol. 40, no. 10-12, pp. 1489-1506, 2000.
7. L. Zhang, M.H. Tong, T.K. Marks, H. Shan, and G.W. Cottrell, "SUN: A Bayesian framework for saliency using natural statistics," J. of Vision, vol. 8, no. 7, pp. 32, 2008.
8. H. J. Seo and P. Milanfar, "Static and space-time visual saliency detection by self-resemblance," J. of Vision, vol. 9, no. 12, pp. 1-27, 2009.
9. T. Kadir and J.M. Brady, "Scale, saliency and scene description," IJCV, vol. 45, no. 2, 2001.
10. N. Bruce and J.K. Tsotsos, "Saliency, attention, and visual search: An information theoretic approach," Journal of Vision, vol. 9, no. 3, 2009.
11. D. Gao, S. Han, and N. Vasconcelos, "Discriminant saliency, the detection of suspicious coincidences, and applications to visual recognition," IEEE PAMI, vol. 31, no. 6, pp. 989-1005, 2009.
12. L. Itti and P. Baldi, "Bayesian surprise attracts human attention," Vision Research, vol. 49, no. 10, pp. 1295-1306, 2009.
13. Z.Wang, A.C. Bovik, H.R. Sheikh, and E.P. Simoncelli, "Image quality assessment: From error visibility to structural similarity," IEEE IP, vol. 13, no. 4, pp. 600-612, 2004.
14. M. Mancas, Computational Attention: Towards attentive computers, Ph.D. thesis, Faculty of Engineering, Mons, 2007.
15. K. Mikolajczyk, et. al., "A comparison of affine region detectors," IJCV, vol. 65, no. 1, pp. 43-72, 2005.