Emotions play a crucial role in person to person interaction. In recent years, there has been a growing interest in improving all aspects of interaction between humans and computers. The ability to understand human emotions is desirable for the computer in several applications especially by observing facial expressions. This paper explores a ways of human-computer interaction that enable the computer to be more aware of the userâ€™s emotional expressions we present a approach for the emotion recognition from a facial expression, hand and body posture. Our model uses multimodal emotion recognition system in which we use two different models for facial expression recognition and for hand gesture recognition and then combining the result of both classifiers using a third classifier which give the resulting emotion. Multimodal system gives more accurate result than a signal or bimodal system.

Facial Emotion Recognition Using Context Based Multimodal Approach

Our works deals with the problem of Information Retrieval System (IRS) that integrates the human behaviour. This system must be able to recognize the degree of satisfaction of the user of the result found through its facial expression, its physiological state, its gestures and its voice. For this, we propose in this paper an algorithm for recognizing the emotional state of a user during a search session in order to issue the relevant documents that he needs. We present also, the architecture agent of the envisaged system.

Towards an intelligent information research system based on the human behavior: Recognition of user emotional state

In recent years, there has been a growing interest in improving all aspects of the interaction between humans and computers. It is proved that to succeed an intelligent interaction between human and machine, computer must be able to interact naturally as possible, exactly like human-human communication. Humans interact specially with speech, but he can add other way like body gestures and looks, to better display its emotions. Emotions can be expressed by visual, vocal, and other physiological means. In this paper, based on body gestures, we discuss a new intelligent approach to detect user emotion.

A new approach to emotion recognition

Recently, all aspects of human computer interaction in the multimedia frameworks, try to be adapted with all feedbacks that can be detected from users. This adaptation can take the name of a social dimension. Amongst these feedbacks, the most important and the most credible we find the emotional back. In that topic this paper deals with the problem of Multimedia Emotion Recognition System (MERS). Based on real time analysis, of non verbal upper body expressive gestures; our system try to compute a probability of the emotional state of a user using simple multimedia peripherals.

Real-time analysis of non-verbal upper-body expressive gestures

Facial emotions are the nonverbal form of communication and we find it very useful when we have no words to express our feelings then we use the gestures to express the same. To detect and track emotions dynamically, we have to use Kinect Sensor since it has camera to produce 3D depth maps. The Facial emotions are detected in real-time, by applying the mesh over the tracked face and thereby identifying the desired points for extracting the features. Facial Action Code Systems (FACS) and Facial Animated Parameters (FAP) are the places of interest for depicting the emotions. Second Life is the 3D Virtual world where people are able to create a digital character called `Avatar' and thereby interacting with the people in the virtual world. The Avatar, which shows some gestures, needs some emotions in a particular scenario. Using the real-time facial emotion recognition based on Kinect depth sensor, avatar emotions are also generated in the 3D Virtual world using Second Life. This idea can be further extended to serve as a communication link so that speech and hearing impaired people can express their emotions.

A real time facial emotion recognition using depth sensor and interfacing with Second Life based Virtual 3D avatar

Emotions recognition is a young field, where a growing maturity implies new needs in terms of modelling and integration in the existing models. Based on our previous work (EMASPEL) and expressive gesture analysis; this paper deals with the problem of Emotion Recognition System (ERS); using a camera and no other special tools, we suggest an architecture for an embedded ERS with learner motion analyses detected in a learning framework.

Real-time learner expressive gestures analysis using in EMASPEL framework

For different reasons, many viewers like to watch a summary of films without having to waste their time. Traditionally, video film was analyzed manually to provide a summary of it, but this costs an important amount of work time. Therefore, it has become urgent to propose a tool for the automatic video summarization job. The automatic video summarization aims at extracting all of the important moments in which viewers might be interested. All summarization criteria can differ from one video to another. This paper presents how the emotional dimensions issued from real viewers can be used as an important input for computing which part is the most interesting in the total time of a film. Our results, which are based on lab experiments that were carried out, are significant and promising.

/pdf/viewer-s-affective-feedback-for-video-summarization-4qk4vuyxa5.pdf

Viewer’s Affective Feedback for Video Summarization

For different reasons, many viewers like to watch a summary of films in less time than it takes to play. Traditionally, video films were analyzed manually to provide its summary; however this requires an important work time. Therefore, it is a necessity to propose a tool for summarization and video analysis automatically. Automatic video summarization has to extract all important moments in which viewers may be interested. All summarization criteria can be different from a video to another. In a different context with foregoing video summarization works, this paper present how the emotional dimensions issued from the real viewers can be considered as the important input to compute which part is most interesting in the total time of a film.

Majdi Dammak

Papers

Real-time learner expressive gestures analysis using in EMASPEL framework

A new approach to emotion recognition

Real-time analysis of non-verbal upper-body expressive gestures

Viewer’s Affective Feedback for Video Summarization

Video summarization using viewer affective feedback