标题：SALIENCY DETECTION BY ADAPTIVE CLUSTERING
作者：Cao, Hai; Li, Shaozi; Su, Songzhi; Cheng, Yun; Ji, Rongrong
作者机构：[Cao, Hai; Li, Shaozi; Su, Songzhi; Ji, Rongrong] Xiamen Univ, Dept Cognit Sci, Xiamen, Peoples R China.; [Cao, Hai; Li, Shaozi; Su, Songzhi; Ji, Ro 更多
会议名称：IEEE International Conference on Visual Communications and Image Processing (VCIP)
会议日期：NOV 17-20, 2013
来源：2013 IEEE INTERNATIONAL CONFERENCE ON VISUAL COMMUNICATIONS AND IMAGE PROCESSING (IEEE VCIP 2013)
关键词：Saliency detection; adaptive clustering; visual attention; image; processing
摘要：Saliency detection plays an important role in image segmentation, content-aware resizing and object recognition. Most approaches obtain promising performance recently, which is useful for the postprocessing. We propose a clustering-based method to detect refined regions with comparative performance For coarse-grained classification with unknown clusters number, an adaptive algorithm called f-means is developed in this paper. Pixels are clustered by f-means based on color and spatial features, and then the centroids are used to compute their saliency values. Experiments show that our algorithm generates more fine maps, which outperform the state-of-the-art approaches on MSRA dataset. Relying on the saliency map, we also get superior results in foreground extracting, image resizing and thumbnails generation.