Abstract
Compared with traditional mono-view video, three-dimensional video (3DV) provides user interactive functionalities and stereoscopic perception, which makes people more interested in pop-out regions or the regions with small depth value. Thus, traditional visual attention model for mono-view video can hardly be directly applied to stereoscopic visual attention (SVA) analysis for 3DV. In this paper, we propose a bottom-up SVA model to simulate human visual system with stereoscopic vision more accurately. The proposed model is based on multiple perceptual stimuli including depth information, luminance, color, orientation and motion contrast. Then, a depth based dynamic fusion is proposed to integrate these features. The experimental results on multi-view video test sequences show that the proposed model maintains high robustness and is able to efficiently simulate SVA of human eyes.
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Zhang, Y., Jiang, G., Yu, M., Chen, K. (2010). Stereoscopic Visual Attention Model for 3D Video. In: Boll, S., Tian, Q., Zhang, L., Zhang, Z., Chen, YP.P. (eds) Advances in Multimedia Modeling. MMM 2010. Lecture Notes in Computer Science, vol 5916. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11301-7_33
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DOI: https://doi.org/10.1007/978-3-642-11301-7_33
Publisher Name: Springer, Berlin, Heidelberg
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