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Kit de desarrollo de software para reconocimiento personalizado del estado de ánimo mediante análisis por vídeo de expresiones faciales

Resumen

Tipo:
Oferta Tecnológica
Referencia:
TOES20190718001
Publicado:
02/08/2019
Caducidad:
02/08/2020
Resumen:
Un grupo de investigación en informática de una universidad española ha desarrollado un nuevo método capaz de reconocer el estado de ánimo de una persona mediante el análisis por vídeo de sus expresiones faciales. Este método ha sido integrado en un kit de desarrollo de software (SDK) para desarrolladores (web y móvil) en campos como investigación de mercados, educación y juegos. Actualmente existen tecnologías para analizar las emociones pero no existen métodos capaces de analizar el estado de ánimo. Este método se basa en el aprendizaje automático de modelos de expresión facial personalizados de cada individuo. La tecnología puede implementarse en diferentes sistemas informáticos o dispositivos móviles y realiza el análisis en tiempo casi real. El grupo de investigación busca socios con el fin de establecer acuerdos de comercialización con asistencia técnica y licencia.

Details

Tittle:
A Software Development Kit for personalized mood recognition through video analysis of facial expressions
Summary:
A Spanish research group in computer science has developed a new method capable of recognizing the mood of a person through a video analysis of facial expressions. This method has been embedded in an Software Development Kit (SDK) for developers (web and mobile) in fields such as market research, education, gaming. Commercial agreements with technical assistance, and license agreements are being sought.
Description:
Facial expression recognition has been widely applied in the field of psychology, video games, health, learning and man-machine interactions in general, being a very active research area.

The concepts of "mood" and "emotion" are often confused in colloquial language and in their formal definitions. However, there is a consensus that marks at least two major differences between these concepts:
· Moods have a longer duration than emotions.
· Moods are related to emotions because a person who is in a certain mood is prone to experience emotions in his/her facial expression.

Current technologies analyze emotions, but they are not able to analyze moods. This method is based on the machine learning of personalized facial expression models for each subject. Once trained, the method performs a dynamic evaluation of the contribution of subject´s facial micro expressions to a certain mood.

This method could be implemented in different computer-based systems or in mobile devices by means of a proprietary SDK and it performs in real time.
Advantages and Innovations:
Currently there are tools that can analyze people´s emotions, but they are not able to analyze and evaluate one´s mood.

The existing tools use procedures that focus on the recognition and processing of snapshots, while this SDK is based on video sequences, which allows to dynamically evaluate the mood in real time.

An important innovation is that the SDK offers a subject´s personalization to minimize errors of different subjects´ micro expressions to express their feelings, for this reason, the method of recognition is precise and customizable.

Existing methods are restricted to the identification of emotions (happiness, sadness, etc.) but do not allow the detection of complex constructs such as mood, the activation of which can at the same time comprise different configurations of emotions, sometimes even opposing ones (for example, anxiety can occur in a sad or in happy person). This method solves the problem, giving way to a much more precise analysis and recognition.
Stage of Development:
Available for demonstration
IPs:
Other
CommeR Statunts Regarding IPR Status:
Propietary software (SDK)

Partner sought

Type and Role of Partner Sought:
This technology can be useful for marketing companies willing to offer product strategies based on customer experience, in the education sector (for on-line courses) and for game development to adjust the games´ playability and engagement.

Client

Type and Size of Client:
University
Already Engaged in Trans-National Cooperation:
No
Languages Spoken:
English
Spanish

Keywords

Technology Keywords:
01004001 Applications for Health
01003003 Artificial Intelligence (AI)
01003012 Imaging, Image Processing, Pattern Recognition