Abstract
Depth is an important feature channel for natural vision organisms that helps in focusing attention on important locations of the viewed scene. Artificial visual attention systems require a fast estimation of depth to construct a saliency map based upon distance from the vision system. Recent studies on depth perception in biological vision indicate that disparity is computed using object detection in the brain. The proposed method exploits these studies and determines the shift that objects go through in the stereo frames using data regarding their borders. This enables efficient creation of depth saliency map for artificial visual attention. Results of the proposed model have shown success in selecting those locations from stereo scenes that are salient for human perception in terms of depth.
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References
Wolfe, J.M., Horowitz, T.S.: What attributes guide the deployment of visual attention and how do they do it? Nature Reviews. Neuroscience 5, 495–501 (2004)
Zhang, Y., Jiang, G., Yu, M., Chen, K.: Stereoscopic visual attention model for 3d video. In: Boll, S., Tian, Q., Zhang, L., Zhang, Z., Chen, Y.-P.P. (eds.) MMM 2010. LNCS, vol. 5916, pp. 314–324. Springer, Heidelberg (2010)
Jang, Y.M., Ban, S.W., Lee, M.: Stereo saliency map considering affective factors in a dynamic environment. In: Ishikawa, M., Doya, K., Miyamoto, H., Yamakawa, T. (eds.) ICONIP 2007, Part II. LNCS, vol. 4985, pp. 1055–1064. Springer, Heidelberg (2008)
Frintrop, S., Rome, E., Nüchter, A., Surmann, H.: A bimodal laser-based attention system. Computer Vision and Image Understanding 100(1-2), 124–151 (2005)
Backus, B.T., Fleet, D.J., Parker, A.J., Heeger, D.J.: Human cortical activity correlates with stereoscopic depth perception. Journal of Neurophysiology 86, 2054–2068 (2001)
Georgieva, S., Peeters, R., Kolster, H., Todd, J.T., Orban, G.A.: The processing of three-dimensional shape from disparity in the human brain. Journal of Neuroscience 29(3), 727–742 (2009)
López-Aranda, M.F., López-Téllez, J.F., Navarro-Lobato, I., Masmudi-Martín, M., Gutiérrez, A., Khan, Z.U.: Role of layer 6 of v2 visual cortex in object-recognition memory. Science 325(5936), 87–89 (2009)
Fang, F., Boyaci, H., Kersten, D.: Border ownership selectivity in human early visual cortex and its modulation by attention. Journal of Neuroscience 29(2), 460–465 (2009)
Nakayama, K., Shimojo, S., Silverman, G.: Stereoscopic depth: its relation to image segmentation, grouping, and the recognition of occluded objects. Perception 18(1), 55–68 (1989)
Peterson, M.A.: Organization, segregation and object recognition. Intellectica 28(1), 37–53 (1999)
Mitsudo, H., Nakamizo, S., Ono, H.: Greater depth seen with phantom stereopsis is coded at the early stages of visual processing. Vision Research 45, 1365–1374 (2005)
van Ee, R., Erkelens, C.: Anisotropy in werner’s binocular depth-contrast effect. Vision research 36, 2253–2262 (1996)
Jost, T., Ouerhani, N., Wartburg, R.v., Müri, R., Hügli, H.: Contribution of depth to visual attention: comparison of a computer model and human. In: Early Cognitive Vision Workshop, Isle of Skye, Scotland (2004)
Tagichi, Y., Wilburn, B., Zitnick, C.L.: Stereo reconstruction with mixed pixels using adaptive over-segmentation. In: CVPR 2008, Alaska, USA, pp. 1–8. IEEE, Los Alamitos (2008)
Wanng, Z.F., Zheng, Z.G.: A region based matching algorithm using cooperative optimization. In: CVPR 2008, Alaska, USA, pp. 1–8. IEEE, Los Alamitos (2008)
Klaus, A., Sormann, M., Karner, K.: Segment-based stereo matching using belief propagation and a self-adapting dissimilarity measure. In: ICPR 2006, pp. 15–18 (2006)
Liu, T., Zhang, P., Luo, L.: Dense stereo correspondence with contrast context histogram, segmentation-based two-pass aggregation and occlusion handling. In: Wada, T., Huang, F., Lin, S. (eds.) PSIVT 2009. LNCS, vol. 5414, pp. 449–461. Springer, Heidelberg (2009)
Tombari, F., Mattocia, S., Stefano, L.D.: Segmentation-based adaptive support for accurate stereo correspondence. In: Mery, D., Rueda, L. (eds.) PSIVT 2007. LNCS, vol. 4872, pp. 427–438. Springer, Heidelberg (2007)
Brockers, R., Hund, M., Mertsching, B.: A fast cost relaxation stereo algorithm with occlusion detection for mobile robot applications. In: VMV, pp. 47–53 (2004)
Brockers, R., Hund, M., Mertsching, B.: Stereo matching with occlusion detection using cost relaxation. In: ICIP, vol. (3), pp. 389–392 (2005)
Aziz, M.Z., Stemmer, R., Mertsching, B.: Region-based depth feature map for visual attention in autonomous mobile systems. In: AMS 2005, Stuttgart - Germany, Informatic Actuell, pp. 89–95. Springer, Heidelberg (2005)
Shafik, M.S.E.N., Mertsching, B.: Real-time scan-line segment based stereo vision for the estimation of biologically motivated classifier cells. In: Mertsching, B., Hund, M., Aziz, Z. (eds.) KI 2009. LNCS, vol. 5803, pp. 89–96. Springer, Heidelberg (2009)
Scharstein, D., Szeliski, R.: A taxonomy and evaluation of dense two-frame stereo correspondence algorithms. International Journal of Computer Vision 47, 7–42 (2001)
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Aziz, M.Z., Mertsching, B. (2010). Fast Depth Saliency from Stereo for Region-Based Artificial Visual Attention. In: Blanc-Talon, J., Bone, D., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2010. Lecture Notes in Computer Science, vol 6474. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17688-3_35
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DOI: https://doi.org/10.1007/978-3-642-17688-3_35
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