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Spotting Rapid Facial Movements from Videos Using Appearance-Based Feature Difference Analysis

机译:使用基于外观的特征差异分析来发现视频的快速面部运动

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摘要

Spotting micro-expressions is a primary step for continuous emotion recognition from videos. Spotting in this context refers to automatically finding the temporal locations of the face-related events from a video sequence. Rapid facial movements mainly include micro-expressions and eye blinks. However, the role of eye blinks in expressing emotions is still controversial, and often they are considered as micro-expressions as well. In this paper a simple method for automatically spotting rapid facial movements from videos is proposed. The method relies on analyzing differences in appearance-based features of sequential frames. In addition to finding the temporal locations, the system is able to provide spatial information about the movements in the face. Micro-expression spotting experiments are carried out on three datasets consisting only of spontaneous micro-expressions. Baseline micro-expression spotting results are provided for these three datasets including the publicly available CASME database. Also an example of spatial localization of the spotted rapid movements is presented.
机译:发现微表达是来自视频的持续情绪识别的主要步骤。在此上下文中发现,指自动从视频序列找到与面部相关事件的时间位置。快速面部运动主要包括微表达和眼睛闪烁。然而,眼睛眨眼表达情绪的作用仍然是争议的,并且通常它们也被视为微表达。在本文中,提出了一种从视频中自动发现快速面部运动的简单方法。该方法依赖于分析顺序框架的外观特征差异。除了找到时间位置之外,系统还能够提供关于面部运动的空间信息。微表达发现实验在仅由自发微表达组成的三个数据集上进行。为这三个数据集提供基线微表达发现结果,包括公开可用的Casme数据库。还提出了斑点快速运动的空间定位的示例。

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