List of results published directly linked with the projects co-funded by the Spanish Ministry of Economy and Competitiveness under the María de Maeztu Units of Excellence Program (MDM-2015-0502).

List of publications acknowledging the funding in Scopus.

The record for each publication will include access to postprints (following the Open Access policy of the program), as well as datasets and software used. Ongoing work with UPF Library and Informatics will improve the interface and automation of the retrieval of this information soon.

The MdM Strategic Research Program has its own community in Zenodo for material available in this repository   as well as at the UPF e-repository   

 

 

Back Sukno FM, Domínguez M, Ruiz A, Schiller D, Lingenfelser F, Pragst L, Kamateri E, Vrochidis S. A Multimodal Annotation Schema for Non-Verbal Affective Analysis in the Health-Care Domain. MARMI'16: 1st International Workshop on Multimedia Analysis and Retrieval for Multimodal Interaction Proceedings

Sukno FM, Domínguez M, Ruiz A, Schiller D, Lingenfelser F, Pragst L, Kamateri E, Vrochidis S. A Multimodal Annotation Schema for Non-Verbal Affective Analysis in the Health-Care Domain. MARMI'16: 1st International Workshop on Multimedia Analysis and Retrieval for Multimodal Interaction Proceedings.

 

The development of conversational agents with human interaction capabilities requires advanced affective state recognition integrating non-verbal cues from the different modalities constituting what in human communication we perceive as an overall affective state. Each of the modalities is often handled by a different subsystem that conveys only a partial interpretation of the whole and, as such, is evaluated only in terms of its partial view. To tackle this shortcoming, we investigate the generation of a unified multimodal annotation schema of non-verbal cues from the perspective of an inter-disciplinary group of experts. We aim at obtaining a common ground-truth with a unique representation using the Valence and Arousal space and a discrete non-linear scale of values. The proposed annotation schema is demonstrated on a corpus in the health-care domain but is scalable to other purposes. Preliminary results on inter-rater variability show a positive correlation of consensus level with high (absolute) values of Valence and Arousal as well as with the number of annotators labeling a given video sequence.

Additional material:

Postprint in UPF e-repository