19 June 2017 Multiple images segmentation based on saliency map
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Proceedings Volume 10443, Second International Workshop on Pattern Recognition; 104430N (2017) https://doi.org/10.1117/12.2280275
Event: Second International Workshop on Pattern Recognition, 2017, Singapore, Singapore
Aiming at discovering and segmenting out common objects from multiple images, co-segmentation is a effective method. It is more accurate to make full use of the relationships between images in segmenting than only single image. The first step is to deal with single image with employing hierarchical segmentation to get a Contour Map, saliency detection to obtain the saliency map and object detection to find the possible common part. Then, constructing a digraph with the multiple local regions, and dealing with the digraph. When a digraph is constructed, the corresponding between adjacent two images is influential to the co-segmentation results. This paper develops a method to sort the images to co-segment. Also, we test the method on ICOSEG and MSRC datasets, and compare it with four proposed method. And the results show that it is efficient in co-segmentation with higher precision than many existing and conventional co-segmentation methods.
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XiaoLan Ning, XiaoLan Ning, Cheng Xu, Cheng Xu, SiQi Li, SiQi Li, ShiYing Li, ShiYing Li, ZhiQi Li, ZhiQi Li, } "Multiple images segmentation based on saliency map", Proc. SPIE 10443, Second International Workshop on Pattern Recognition, 104430N (19 June 2017); doi: 10.1117/12.2280275; https://doi.org/10.1117/12.2280275

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