A Joint Salience Detection Algorithm Based on Multi-image Foreground Correspondence

Abstract

Abstract: A joint salience detection algorithm based on foreground correspondence for multiple images is proposed to filter the redundant information in the image. The accurate foreground region is selected from the convex hull by using the boundary continuity, and then the corresponding foreground region is fused with the background based salience map to generate the final joint salience map. The results show that the minimum value of joint salience map can reach 0.071 because of other algorithms and the MAE value of single detection salience map, which indicates that the foreground correspondence salience detection algorithm combined with background has good detection ability in multi-image detection, and has important research significance and application prospect in the field of computer vision.

Key words: multi image, foreground, joint salience, salience detection

CLC Number:

TP391

LIU Lei. A Joint Salience Detection Algorithm Based on Multi-image Foreground Correspondence[J]. Journal of Qujing Normal University, 2022, 41(3): 75-81.

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