Image visual attention computation and application via the learning of object attributes

Machine Vision and Applications

Volumn 25, Issue 7, 2014, Pages 1671-1683

  Han, Junwei ^a   Wang, Dongyang ^a   Shao, Ling ^b   Qian, Xiaoliang ^a   Cheng, Gong ^a   Han, Jungong ^c  

^a NORTHWESTERN POLYTECHNICAL UNIVERSITY   (China)

^b UNIVERSITY OF SHEFFIELD   (United Kingdom)

^c Civolution   (Netherlands)

Author keywords

Eye tracking; Image categorization; Object bank; Visual attention

Indexed keywords

COMPUTATION THEORY; DIGITAL STORAGE; EYE MOVEMENTS; IMAGING SYSTEMS; OBJECT RECOGNITION; PIXELS; PROBLEM SOLVING;

ALLOCATION OF ATTENTIONS; COMPREHENSIVE EVALUATION; EYE-TRACKING; IMAGE CATEGORIZATION; OBJECT BANK; STATE-OF-THE-ART METHODS; VISUAL ATTENTION; VISUAL ATTENTION MODEL;

BEHAVIORAL RESEARCH;

EID: 84920249705     PISSN: 09328092     EISSN: 14321769     Source Type: Journal    
DOI: 10.1007/s00138-013-0558-1     Document Type: Article

References (49)

1. Achanta, R., Estrada, F., Wils, P., Süsstrunk, S.: Salient region detection and segmentation. In: ICVS, pp. 66–75 (2008)
2. Achanta, R., Hemami, S., Estrada, F., Susstrunk, S.: Frequency-tuned salient region detection. In: CVPR, pp. 1597–1604 (2009)
3. Alexe, B., Deselaers, T., Ferrari, V.: What is an object? In: CVPR, pp. 73–80 (2010)
4. Bruce, N., Tsotsos, J.: Saliency based on information maximization. In: NIPS, pp. 155–162 (2006)
5. Chen, Z., Han, J., Ngan, K.N.: Dynamic bit allocation for multiple video object coding. IEEE Trans. Multimed. 8(6), 1117–1124 (2006)
6. Cheng, M.M., Zhang, G.X., Mitra, N.J., Huang, X., Hu, S.M.: Global contrast based salient region detection. In: CVPR, pp. 409–416 (2011)
7. Einhäuser, W., Spain, M., Perona, P.: Objects predict fixations better than early saliency. J. Vis. 8(14), 1–26 (2008)
8. Felzenszwalb, P.F., Girshick, R.B., McAllester, D., Ramanan, D.: Object detection with discriminatively trained part-based models. IEEE Trans. Pattern Anal. Mach. Intell. 32(9), 1627–1645 (2010)
9. Gao, D., Mahadevan, V., Vasconcelos, N.: On the plausibility of the discriminant center-surround hypothesis for visual saliency. J. Vis. 8(7), 1–18 (2008)
10. Goferman, S., Zelnik-Manor, L., Tal, A.: Context-aware saliency detection. In: CVPR, pp. 2376–2383 (2010)
11. Gopalakrishnan, V., Hu, Y., Rajan, D.: Salient region detection by modeling distributions of color and orientation. IEEE Trans. Multimed. 11(5), 892–905 (2009)
12. Guo, C., Ma, Q., Zhang, L.: Spatio-temporal saliency detection using phase spectrum of quaternion fourier transform. In: CVPR, pp. 1–8 (2008)
13. Han, B., Zhu, H., Ding, Y.: Bottom-up saliency based on weighted sparse coding residual. In: ACM Multimedia, pp. 1117–1120 (2011)
14. Han, J., Ngan, K.N., Li, M., Zhang, H.J.: Unsupervised extraction of visual attention objects in color images. IEEE Trans. Circuit. Syst. Video Technol. 16(1), 141–145 (2006)
15. Han, J., Pauwels, E., Zeeuw, P.: Fast saliency-aware multi-modality image fusion. Neurocomputing 111, 70–80 (2013)
16. Harel, J., Koch, C., Perona, P.: Graph-Based Visual Saliency. In: NIPS, pp. 545–552 (2007)
17. Hoiem, D., Efros, A.A., Hebert, M.: Automatic photo pop-up. ACM Trans. Graphics 24, 577–584 (2005)
18. Hou, X., Zhang, L.: Saliency detection: a spectral residual approach. In: CVPR, pp. 1–8 (2007)
19. Hou, X., Harel, J., Koch, C.: Image signature: highlighting sparse salient regions. IEEE Trans. Pattern Anal. Mach. Intell. 34(1), 194–201 (2012)
20. Itti, L., Koch, C., Niebur, E.: A model of saliency-based visual attention for rapid scene analysis. IEEE Trans. Pattern Anal. Mach. Intell. 20(11), 1254–1259 (1998)
21. Itti, L., Koch, C.: A saliency-based search mechanism for overt and covert shifts of visual attention. Vis. Res. 40(10–12), 1489–1506 (2000)
22. Jiang, P., Qin, X.: Keyframe-based video summary using visual attention clues. IEEE MultiMed. 17(2), 64–73 (2010)
23. Judd, T., Ehinger, K., Durand, F., Torralba, A.: Learning to predict where humans look. In: ICCV, pp. 2106–2113 (2009)
24. Khuwuthyakorn, P., Robles-Kelly, A., Zhou, J.: Object of interest detection by saliency learning. In: ECCV, pp. 636–649 (2010)
25. Lazebnik, S., Schmid, C., Ponce, J.: Beyond bags of features: spatial pyramid matching for recognizing natural scene categories. In: CVPR, pp. 2169–2178 (2006)
26. Le Meur, O., Le Callet, P., Barba, D., Thoreau, D.: A coherent computational approach to model bottom-up visual attention. IEEE Trans. Pattern Anal. Mach. Intell. 28(5), 802–817 (2006)
27. Le Meur, O., Baccino, T., Roumy, A.: Prediction of the inter-observer visual congruency (IOVC) and application to image ranking. In: ACM Multimedia, pp. 373–382 (2011)
28. Lee, W.F., Huang, T.H., Yeh, S.L., Chen, H.H.: Learning-based prediction of visual attention for video signals. IEEE Trans. Image Process. 20(11), 3028–3038 (2011)
29. Li, L.J., Su, H., Lim, Y., Fei-Fei, L.: Objects as attributes for scene classification. In: ECCV, pp. 1–13 (2010)
30. Liu, F., Gleicher, M.: Video retargeting: automating pan and scan. In: ACM Multimedia, pp. 241–250 (2006)
31. Liu, T., Wang, J., Sun, J., Zheng, N., Tang, X., Shum, H.Y.: Picture collage. IEEE Trans. Multimed. 11(7), 1225–1239 (2009)
32. Liu, T., Yuan, Z., Sun, J., Wang, J., Zheng, N., Tang, X., Shum, H.Y.: Learning to detect a salient object. IEEE Trans. Pattern Anal. Mach. Intell. 33(2), 353–367 (2011)
33. Ma, Y.F., Lu, L., Zhang, H.J., Li, M.: A user attention model for video summarization. In: ACM Multimedia, pp. 533–542 (2002)
34. Ma, Y.F., Zhang, H.J.: Contrast-based image attention analysis by using fuzzy growing. In: ACM Multimedia, pp. 374–381 (2003)
35. Ngo, C.W., Ma, Y.F., Zhang, H.J.: Video summarization and scene detection by graph modeling. IEEE Trans. Circuit. Syst. Video Technol. 15(2), 296–305 (2005)
36. Nuthmann, A., Henderson, J.M.: Object-based attentional selection in scene viewing. J. Vis. 10(8), 1–19 (2010)
37. Oliva, A., Torralba, A.: Modeling the shape of the scene: a holistic representation of the spatial envelope. Int. J. Comput. Vis. 42(3), 145–175 (2001)
38. Seo, H.J., Milanfar, P.: Static and space-time visual saliency detection by self-resemblance. J. Vis. 9(12), 1–27 (2009)
39. Shao, L., Brady, M.: Specific object retrieval based on salient regions. Pattern Recognit. 39(10), 1932–1948 (2006)
40. Shao, L., Kadir, T., Brady, M.: Geometric and photometric invariant distinctive regions detection. Inf. Sci. 177(4), 1088–1122 (2007)
41. Subramanian, R., Yanulevskaya, V., Sebe, N.: Can computers learn from humans to see better?: inferring scene semantics from viewers’ eye movements. In: ACM Multimedia, pp. 33–42 (2011)
42. Tatler, B.W., Hayhoe, M.M., Land, M.F., Ballard, D.H.: Eye guidance in natural vision: reinterpreting salience. J. Vis. 11(5), 1–23 (2011)
43. Torralba, A., Oliva, A., Castelhano, M.S., Henderson, J.M.: Contextual guidance of eye movements and attention in real-world scenes: the role of global features in object search. Psychol. Rev. 113(4), 766–786 (2006)
44. Wang, L., Xue, J., Zheng, N., Hua, G.: Automatic salient object extraction with contextual cue. In: ICCV, pp. 105–112 (2011)
45. Han, J., He, S., Qian, X., Wang, D., Guo, L., Liu, T.: An object-oriented visual saliency detection framework based on sparse coding representations. IEEE Trans. Circuit. Syst. Video Technol. (2013)
46. Han, J., Shao, L., Xu, D., Shotton, J.: Enhanced computer vision with Microsoft Kinect sensor: a review. IEEE Trans. Cybern. 43(5), 1318–1334 (2013)
47. Hong, R., Tang, J., Tan, H., Ngo, C., Yan, S., Chua, T.: Beyond search: event-driven summarization for web videos. TOMCCAP 7(4), 35 (2011)
48. Wang, M., Hong, R., Li, G., Zha, Z., Yan, S., Chua, T.: Event driven web video summarization by tag localization and key-shot identification. IEEE Trans. Multimed. 14(4), 975–985 (2012)
49. Hong, R., Wang, M., Li, G., Nie, L., Zha, Z., Chua, T.: Multimedia question answering. IEEE Multimed. 19(4), 72–78 (2012)