计算机应用与软件2017，Vol.34Issue(8)：213-219,235,8.DOI:10.3969/j.issn.1000-386x.2017.08.038
显著性目标检测中的视觉特征及融合
VISUAL FEATURE AND FUSION OF SALIENCY OBJECT DETECTION
摘要
Abstract
The saliency object detection is a very important step in many computer vision problems, including video image segmentation, target recognition, and has a very broad application prospect.Over the past 10 years of development of the apparent test model, it can be clearly seen that most of the detection methods are detected by using visual features, and the visual characteristics determine the performance and effectiveness of the significance test model.One of the fundamental differences between the various saliency detection models is the chosen of visual features.We reviewed and summarized the common visual features for the first time, such as color, texture and background.We classified them, compared and analyzed them.Firstly, we selected the better features from all kinds of color features to fuse, and then compared the color features with other characteristics, and chosen the best features to fuse.On the challenging open datasets ESSCD and DUT-OMON, the quantitative comparison was made from three aspects: PR curve, F-measure method and MAE mean error, and the comprehensive effect was better than other algorithms.By comparing and merging different visual features, it is shown that the four characteristics of color, texture, border connectivity and Objectness are very effective in the saliency object detection.关键词
显著性检测/视觉特征/特征融合/显著图Key words
Saliency detection/Visual feature/Feature fusion/Saliency map分类
信息技术与安全科学引用本文复制引用
袁小艳,王安志,潘刚,王明辉..显著性目标检测中的视觉特征及融合[J].计算机应用与软件,2017,34(8):213-219,235,8.基金项目
国家重点研究与发展计划项目(2016YFB0700802,2016YFB0800600) （2016YFB0700802,2016YFB0800600）
国家海洋局海洋遥感工程技术研究中心创新青年项目(2015001). （2015001）
