Pain expression recognition based on pLSA model.

Shaoping Zhu

doi:10.1155/2014/736106

Abstract

We present a new approach to automatically recognize the pain expression from video sequences, which categorize pain as 4 levels: “no pain,” “slight pain,” “moderate pain,” and “ severe pain.” First of all, facial velocity information, which is used to characterize pain, is determined using optical flow technique. Then visual words based on facial velocity are used to represent pain expression using bag of words. Final pLSA model is used for pain expression recognition, in order to improve the recognition accuracy, the class label information was used for the learning of the pLSA model. Experiments were performed on a pain expression dataset built by ourselves to test and evaluate the proposed method, the experiment results show that the average recognition accuracy is over 92%, which validates its effectiveness.

Highlights

IntroductionTremendous amounts of researches have been carried out in the field of automatic expressions (such as pain, anger, and sadness) recognition from video sequence
In recent years, tremendous amounts of researches have been carried out in the field of automatic expressions recognition from video sequence
In order to improve the recognition accuracy, the class label information was used for the learning of the Probabilistic Latent Semantic Analysis (pLSA) model

Summary

Introduction

Tremendous amounts of researches have been carried out in the field of automatic expressions (such as pain, anger, and sadness) recognition from video sequence. Measuring or monitoring pain is normally conducted via self-report as it is convenient and requires no special skill or staffing. Self-report measures cannot be used when patients cannot communicate verbally. Many researchers have pursued the goal of obtaining a continuous objective measure of pain through analyses of tissue pathology, neurological “signatures,” imaging procedures, testing of muscle strength, and so on [3]. These approaches have been fraught with difficulty because they are often inconsistent with other evidence of pain [3], in addition to being highly invasive and constraining to the patient

Objectives

Methods

Results

Conclusion