background: we determined the levels of subjective and observer drowsiness and facial dynamics changes. methods: this experimental study was done in the virtual reality laboratory of khaje-nasir toosi university of technology in 2015. facial dynamics changes like changes in eyes, mouth and eyebrows were surveyed on twenty-five drivers in 2015bykss (karolinska sleepiness scale) and ord (observer...

This work presents a technique for the analysis of Facial Electromyogram signal activities to classify five different facial expressions for Computer-Muscle Interfacing applications. Facial Electromyogram (FEMG) is a technique for recording the asynchronous activation of neuronal inside the face muscles with non-invasive electrodes. FEMG pattern recognition is a difficult task for the researche...

The muscular activities caused the activation of certain AUs for every facial expression at the certain duration of time throughout the facial expression. This paper presents the methods to recognise facial Action Unit (AU) using facial distance of the facial features which activates the muscles. The seven facial action units involved are AU1, AU4, AU6, AU12, AU15, AU17 and AU25 that characteri...

Facial expressions analysis is a vital part of the research in human-machine interaction. This chapter introduces an automatic recognition system for facial expression from a front view human face image. Obtaining an effective facial representation from initial face images is an essential phase for strong and efficient facial expression system. In this chapter we have developed a facial express...

An emotional scene detection method is proposed in order to retrieve impressive scenes from lifelog videos. The proposed method is based on facial expression recognition considering that a wide variety of facial expression could be observed in impressive scenes. Conventional facial expression techniques, which focus on discriminating typical facial expressions, will be inadequate for lifelog vi...

The field of computer vision endeavours to develop automatic approaches to the interpretation of images from the real world. Over the past number of decades researchers within this field have created systems specifically for the automatic analysis of facial expression. The most successful of these approaches draw on the tools from behavioural science. In this chapter we examine facial expressio...

Research into facial expression recognition has predominantly been based upon near frontal view data. However, a recent 3D facial expression database (BU-3DFE database) has allowed empirical investigation of facial expression recognition across pose. In this paper, we investigate the effects of pose from frontal to profile view on facial expression recognition. Experiments are carried out on 10...

Research into facial expression recognition has predominantly been based upon near frontal view data. However, a recent 3D facial expression database (BU-3DFE database) has allowed empirical investigation of facial expression recognition across pose. In this paper, we investigate the effects of pose from frontal to profile view on facial expression recognition. Experiments are carried out on 10...

Recently, studies of human face recognition have been conducted vigorously (Fasel & Luettin, 2003; Yang et al., 2002; Pantic & Rothkrantz, 2000a; Zhao et al., 2000; Hasegawa et al., 1997; Akamatsu, 1997). Such studies are aimed at the implementation of an intelligent man-machine interface. Especially, studies of facial expression recognition for humanmachine emotional communication are attracti...

Facial expression plays a key role in non-verbal face-to-face communication. It is a challenging task to develop an automatic facial expression reading and understanding system, especially, for recognizing the facial expression from a static image without any prior knowledge of the test subject. In this paper, we present a topographic modeling approach to recognize and analyze facial expression...