计算机工程与应用2019，Vol.55Issue(20)：177-183,191,8.DOI:10.3778/j.issn.1002-8331.1812-0338
基于简单帧选择的显著性检测方法
Saliency Detection Method Based on Simple Frame Selection
摘要
Abstract
This paper proposes a novel video saliency detection method. Firstly, in order to extract features with high con-fidence in the video sequence, a simple frame selection criterion is proposed according to the initial saliency map of the input frame and the input frame, and the simple selection criterion is used to select the video sequence to easily and accurately extract the foreground object, it gets robust foreground background label from simple frames. Then the image is sub-pixel segmented, and the time-space feature and foreground tag input integrated learning model is extracted. After multi-kernel SVM integration learning, a pixel-level saliency map is finally generated, and the motion feature is spread to the entire video set. Experimental results of various video sequences show that the algorithm is superior to the traditional significant detection algorithm in qualitative and quantitative.关键词
简单帧选择/显著性检测/多核SVM集成学习Key words
simple frame selection/saliency detection/multi-kernel SVM bootstrap learning分类
信息技术与安全科学引用本文复制引用
徐屹伟,刘政怡,赵悉超..基于简单帧选择的显著性检测方法[J].计算机工程与应用,2019,55(20):177-183,191,8.基金项目
国家科技支撑计划项目(No.2015BAK24B00) （No.2015BAK24B00）
安徽高校省级自然科学研究项目(No.KJ2015A009). （No.KJ2015A009）
