ABSTRACT
Human vision system understands the environment from 3D perception. However, most existing saliency detection algorithms detect the salient foreground based on 2D image information. In this paper, we propose a saliency detection method using the additional depth information. In our method, saliency cues are provided to follow the laws of the visually salient stimuli in both color and depth spaces. Simultaneously, the 'center bias' is also extended to 'spatial' bias to represent the nature advantage in 3D image. In addition, We build a dataset to test our method and the experiments demonstrate that the depth information is useful for extracting the salient object from the complex scenes.
- R. Achanta, S. Hemami, F. Estrada, and S. Susstrunk. Frequency-tuned salient region detection. In CVPR, pages 1597--1604, 2009.Google ScholarCross Ref
- Z. Chen, J. Yuan, and Y. Tan. Hybrid saliency detection for images. Signal Processing Letters, 20(1):95--98, 2013.Google ScholarCross Ref
- M. Cheng, G. Zhang, N. Mitra, X. Huang, and S. Hu. Global contrast based salient region detection. In CVPR, pages 409--416, 2011. Google ScholarDigital Library
- H. Fu, X. Cao, and Z. Tu. Cluster-based co-saliency detection. IEEE Transactions on Image Processing, 22(10):3766--3778, 2013.Google ScholarDigital Library
- L. Itti, C. Koch, and E. Niebur. A model of saliency-based visual attention for rapid scene analysis. TPAMI, 20(11):1254--1259, 1998. Google ScholarDigital Library
- C. Lang, T. Nguyen, H. Katti, K. Yadati, M. Kankanhalli, and S. Yan. Depth matters: Influence of depth cues on visual saliency. ECCV, pages 101--115, 2012. Google ScholarDigital Library
- S. Liu, Y. Wang, L. Yuan, J. Bu, P. Tan, and J. Sun. Video stabilization with a depth camera. In CVPR, pages 89--95, 2012. Google ScholarDigital Library
- T. Liu, Z. Yuan, J. Sun, N. Z. J. Wang, X. Tang, and H.-Y. Shum. Learning to detect a salient object. TPAMI, 33(2):353--367, 2011. Google ScholarDigital Library
- Y. Niu, Y. Geng, X. Li, and F. Liu. Leveraging stereopsis for saliency analysis. In CVPR, pages 454--461, 2012. Google ScholarDigital Library
- J. Shotton, A. Fitzgibbon, M. Cook, T. Sharp, M. Finocchio, R. Moore, A. Kipman, and A. Blake. Real-time human pose recognition in parts from single depth images. In CVPR, pages 1297--1304, 2011. Google ScholarDigital Library
- H. Simon and B. Richard. Kinecting the dots: Particle based scene flow from depth sensors. In ICCV, pages 2290--2295, 2011. Google ScholarDigital Library
- J. Yan, M. Zhu, H. Liu, and Y. Liu. Visual saliency detection via sparsity pursuit. Signal Processing Letters, 17(8):739--742, 2010.Google ScholarCross Ref
- Q. Yan, L. Xu, J. Shi, and J. Jia. Hierarchical saliency detection. In CVPR, pages 1155--1162, 2013. Google ScholarDigital Library
- C. Yang, L. Zhang, H. Lu, X. Ruan, and M.-H. Yang. Saliency detection via graph-based manifold ranking. In CVPR, pages 3166--3173, 2013. Google ScholarDigital Library
Index Terms
- Depth Enhanced Saliency Detection Method
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