Object-level saliency detection with color attributes
作者：
Highlights：
• We propose an object-level salient detection algorithm which explicitly explores bottom-up visual attention and objectness cues.
• Some category-independent object candidates are firstly segmented from the image by the quantized color attributes of images.
• Global cues and candidate objectness are developed, to evaluate bottom-up visual attention of the whole image and the objectness of the object candidates respectively.
• By explicitly combining local objectness cue with global low-level saliency cues with candidates location and color attributes, our proposed method is more suitable for processing images with complex background.
摘要
•We propose an object-level salient detection algorithm which explicitly explores bottom-up visual attention and objectness cues.•Some category-independent object candidates are firstly segmented from the image by the quantized color attributes of images.•Global cues and candidate objectness are developed, to evaluate bottom-up visual attention of the whole image and the objectness of the object candidates respectively.•By explicitly combining local objectness cue with global low-level saliency cues with candidates location and color attributes, our proposed method is more suitable for processing images with complex background.
论文关键词：Candidate objectness,Global cues,Color attributes,Saliency detection
论文评审过程：Received 8 September 2014, Revised 18 July 2015, Accepted 20 July 2015, Available online 31 July 2015, Version of Record 28 September 2015.
论文官网地址：https://doi.org/10.1016/j.patcog.2015.07.005
