Abstract
The visual salient regions detection is one of the fundamental problems in computer vision, so saliency estimation has become a valuable tool in image processing. In this paper, we propose a novel method to realize the calculation of saliency, using color contrast and connectivity prior (called CCP for short). There are three cues integrated to obtain high-quality map, including contrast, spatial distribution and high-level prior. We evaluate our approach on three standard benchmark datasets with other state-of-the-art approaches, the results show that the proposed method has the higher precision and recall, the final maps are more closed to the ground truth.
This research is partly supported by the National Science Foundation, China (no. 61379065). Hebei Province Science and Technology Support Program, China (no. 13211801D). The Doctoral Foundation of Yanshan University (no. B540)
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Chen, MH., Dou, Y., Zhang, SH. (2015). Salient Region Detection by Region Color Contrast and Connectivity Prior. In: Zha, H., Chen, X., Wang, L., Miao, Q. (eds) Computer Vision. CCCV 2015. Communications in Computer and Information Science, vol 547. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-48570-5_3
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DOI: https://doi.org/10.1007/978-3-662-48570-5_3
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