Abstract

This paper presents a preliminary study concerning a fast preprocessing method for facial microexpression (ME) spotting in video sequences. The rationale is to detect frames containing frozen expressions as a quick warning for the presence of MEs. In fact, those frames can either precede or follow (or both) MEs according to ME type and the subject’s reaction. To that end, inspired by the Adelson–Bergen motion energy model and the instinctive nature of the preattentive vision, global visual perception-based features were employed for the detection of frozen frames. Preliminary results achieved on both controlled and uncontrolled videos confirmed that the proposed method is able to correctly detect frozen frames and those revealing the presence of nearby MEs—independently of ME kind and facial region. This property can then contribute to speeding up and simplifying the ME spotting process, especially during long video acquisitions.

Highlights

  • In the last few years, non verbal communication has gained interest in different fields, such as forensic investigation, security devices, clinical diagnosis, marketing investigation and forecasting, etc

  • This paper presents a preliminary study concerning a fast preprocessing method for facial microexpression (ME) spotting in video sequences

  • To that end, inspired by the Adelson–Bergen motion energy model and the instinctive nature of the preattentive vision, global visual perception-based features were employed for the detection of frozen frames

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Summary

Introduction

In the last few years, non verbal communication has gained interest in different fields, such as forensic investigation, security devices, clinical diagnosis, marketing investigation and forecasting, etc. MEs are characterized by very short durations, ranging from 1/25 to 1/5 of a second (recently relaxed to a maximum duration of 1/2 s) [5] Since this short duration usually goes along with a very low intensity involving just a partial motion, MEs are very difficult to detect by human beings [6]. They have distinctive peculiarities, as highlighted in their original definition [7].

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