Computer Science ›› 2017, Vol. 44 ›› Issue (5): 308-313.doi: 10.11896/j.issn.1002-137X.2017.05.057

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Multi-object Segmentation of Image Scene Based on Object Recognition and Saliency Detection

LI Qing, YUAN Jia-zheng and LIU Hong-zhe   

  • Online:2018-11-13 Published:2018-11-13

Abstract: This paper proposed a multi-object segmentation method of image scene based on object recognition and salien-cy detection.The object detector is learned on the training set,and then is used to locate the object in the test image with visualization of its bounding box.The test image is over-segmented into a set of superpixels.According to the location of bounding box and the superpixel-level propobilities,the region of interest is fixed.Then,a saliency map is obtained through a three-scale saliency detection.In the region of interest,a CRF model is established among the neighbo-ring superpixels,whose nodes indicate the superpixels and edges indicate their neighborhood.The saliency of a superpi-xel is embedded into the weight of relative node,and the feature difference between two neighboring superpixels is embedded into the weight of relative edge.Thus,the multi-object segmentation task is transformed into a multi-labeling task.Finally,the CRF formulation is optimized using graph cut algorithm to get the multi-object segmentation result.The experimental results show the good performance of our method.

Key words: Image segmentation,Semantic labeling,Object reasoning

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