Multiresolution saliency map based object segmentation

Jian Yang; Xin Wang; ZhenYou Dai

doi:10.1117/1.JEI.24.6.061205

17 November 2015 Multiresolution saliency map based object segmentation

Jian Yang, Xin Wang, ZhenYou Dai

Author Affiliations +

Journal of Electronic Imaging, Vol. 24, Issue 6, 061205 (November 2015). https://doi.org/10.1117/1.JEI.24.6.061205

Abstract

Salient objects’ detection and segmentation are gaining increasing research interest in recent years. A saliency map can be obtained from different models presented in previous studies. Based on this saliency map, the most salient region (MSR) in an image can be extracted. This MSR, generally a rectangle, can be used as the initial parameters for object segmentation algorithms. However, to our knowledge, all of those saliency maps are represented in a unitary resolution although some models have even introduced multiscale principles in the calculation process. Furthermore, some segmentation methods, such as the well-known GrabCut algorithm, need more iteration time or additional interactions to get more precise results without predefined pixel types. A concept of a multiresolution saliency map is introduced. This saliency map is provided in a multiresolution format, which naturally follows the principle of the human visual mechanism. Moreover, the points in this map can be utilized to initialize parameters for GrabCut segmentation by labeling the feature pixels automatically. Both the computing speed and segmentation precision are evaluated. The results imply that this multiresolution saliency map-based object segmentation method is simple and efficient.

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Jian Yang, Xin Wang, and ZhenYou Dai "Multiresolution saliency map based object segmentation," Journal of Electronic Imaging 24(6), 061205 (17 November 2015). https://doi.org/10.1117/1.JEI.24.6.061205

Published: 17 November 2015

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