计算机工程与应用2019，Vol.55Issue(8)：40-47,8.DOI:10.3778/j.issn.1002-8331.1901-0359
基于眼动序列分析的眨眼检测
Blink Detection Based on Eyes Motion Sequence Analysis
摘要
Abstract
This paper presents a method for individually describing the video segments with open eyes and those with blink and coarse-to-fine blink detection based on two-stage cascade model composed of sequence-level and frame-level. In sequence-level detection phase, the video segment is condensed and CNN feature is extracted. Optical flow between frames is accumulated and expressed as dynamic feature by Bag of Feature(BoF). The above two features are fused to dis-cover whether blinks exist in the current segment by classification. In frame-level detection phase, the blink motion is described precisely to describe every frame may contain blink by extracting multi-mode features. Eye closity is calculated by random regression forest and the precise blink localization is obtained. Experiments on different datasets show the pro-posed method improves the robustness of blink detection under uncontrolled real environment and reaches an increased performance in correct rate, convergence and speed are under the considerable computational complexity. Compared with the other current methods, the method has significant value in real applications.关键词
序列级检测/帧级检测/多模式特征/随机回归森林Key words
sequence-level detection/ frame-level detection/ multi-mode feature/ random regression forest分类
交通工程引用本文复制引用
高宁,王兴元,王秀坤..基于眼动序列分析的眨眼检测[J].计算机工程与应用,2019,55(8):40-47,8.基金项目
国家自然科学基金(No.61663020) （No.61663020）
国家重点研发计划资助(No.2017YFB1201003-020). （No.2017YFB1201003-020）
