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About

I am a Coordinator Professor at the Polytechnic of Porto and a Researcher at INESC TEC, where I lead the Multimedia Communications Technology Area. I  obtained my PhD from University of Porto in the area of multimedia content management. I have been responsible for the participation of INESC TEC in several national and European projects, involving universities and media industries. Author of several publications, I am also an active reviewer for journals and conferences and engaged in the organization of workshops and program committees in the area of Multimedia. Recently I co-chaired the Immersive Media Experiences workshop series (2013-2015) at ACM MM. Additionally I am also often engaged in the evaluation of European and Portuguese research proposals and projects. My main research activities and interests are in the field of networked audiovisual systems, including digital television and new services, content management, personalization and recomendation, new media formats and immersive and interactive media.

Interest
Topics
Details

Details

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Publications

2021

SmoothMV

Authors
da Costa, TS; Andrade, MT; Viana, P;

Publication
Proceedings of the International Workshop on Immersive Mixed and Virtual Environment Systems (MMVE '21)

Abstract

2021

Inferring Contextual Data from Real-World Photography

Authors
Costa, TS; Andrade, MT; Viana, P;

Publication
Advances in Intelligent Systems and Computing - Intelligent Systems Design and Applications

Abstract

2021

Emotion Identification in Movies through Facial Expression Recognition

Authors
Almeida, J; Vilaca, L; Teixeira, IN; Viana, P;

Publication
Applied Sciences

Abstract
Understanding how acting bridges the emotional bond between spectators and films is essential to depict how humans interact with this rapidly growing digital medium. In recent decades, the research community made promising progress in developing facial expression recognition (FER) methods. However, no emphasis has been put in cinematographic content, which is complex by nature due to the visual techniques used to convey the desired emotions. Our work represents a step towards emotion identification in cinema through facial expressions’ analysis. We presented a comprehensive overview of the most relevant datasets used for FER, highlighting problems caused by their heterogeneity and to the inexistence of a universal model of emotions. Built upon this understanding, we evaluated these datasets with a standard image classification models to analyze the feasibility of using facial expressions to determine the emotional charge of a film. To cope with the problem of lack of datasets for the scope under analysis, we demonstrated the feasibility of using a generic dataset for the training process and propose a new way to look at emotions by creating clusters of emotions based on the evidence obtained in the experiments.

2021

Automatic TV Logo Identification for Advertisement Detection without Prior Data

Authors
Carvalho, P; Pereira, A; Viana, P;

Publication
Applied Sciences

Abstract
Advertisements are often inserted in multimedia content, and this is particularly relevant in TV broadcasting as they have a key financial role. In this context, the flexible and efficient processing of TV content to identify advertisement segments is highly desirable as it can benefit different actors, including the broadcaster, the contracting company, and the end user. In this context, detecting the presence of the channel logo has been seen in the state-of-the-art as a good indicator. However, the difficulty of this challenging process increases as less prior data is available to help reduce uncertainty. As a result, the literature proposals that achieve the best results typically rely on prior knowledge or pre-existent databases. This paper proposes a flexible method for processing TV broadcasting content aiming at detecting channel logos, and consequently advertising segments, without using prior data about the channel or content. The final goal is to enable stream segmentation identifying advertisement slices. The proposed method was assessed over available state-of-the-art datasets as well as additional and more challenging stream captures. Results show that the proposed method surpasses the state-of-the-art.

2020

Learning Physics Through Online Video Annotations

Authors
Marcal, J; Borges, MM; Viana, P; Carvalho, P;

Publication
EDUCATION IN THE KNOWLEDGE SOCIETY

Abstract
The support of video in the learning environment is nowadays used to many ends, for either for demonstration, research or share. It is intended to reinforce the space before and after class and introduce a new dynamic and interaction in the classroom itself. Pedagogical Innovation may be achieved by different approaches to motivate students and obtain better results. The Audiovisual didactic content has been in recent years disseminated, in the Physics domain, mainly through YouTube platform. Many aspects of video production activities can increase students' self-esteem, increase their satisfaction with the learning experience, promote a positive attitude towards the subject, provide students with lower level of understanding with a broad individual tutoring, encouraging students to discuss with each other, exchange their opinions, and compare the results of lab activities. On the other hand, video can support research activities, offering the researcher access to a rich data aggregation to investigate the learning processes. This paper presents a revision of the literature about the potential of using video annotation in the education context and, perspectives of teachers' use of collaborative annotation systems, to promote reflection, specifically in the domain of Physics, using an open source annotation tool. The creation of audiovisual references, either for quick access to parts of organized video annotated content by the teacher, knowledge building or revision by and for other students is analyzed. This study is complemented with a testbed, showing the potential of using audiovisual annotated content, within a k-12 context. Students were invited to select video content, annotate, organize and publish the annotations, which could support the learning process in the domain of Physics. Results show that most of the aspects under analysis received a positive evaluation, and students expressed a gain from oral lectures and access to new sources of learning. The only exception relates to the capacity of the approach to motivated students to the study of Physics, as most of the students did not see this methodology too much motivating. The impact of this research relates to alternative teaching / learning methods, within the Physics' domain, using online video annotation, in the support of traditional exposition and memorization methodologies.

Supervised
thesis

2020

Automatic Emotion Identification: Analysis and Detection of Facial Expressions in Movies

Author
João Carlos Miranda de Almeida

Institution
UP-FEUP

2020

Video-based music generation

Author
Serkan Sulun

Institution
UP-FEUP

2020

Towards a Scalable Dataset Construction for Facial Recognition: A guided data selection approach for diversity stimulation

Author
Luís Miguel Salgado Nunes Vilaça

Institution
IPP-ISEP

2020

Context-Based Cultural Visits

Author
Mariana Figueiredo Moutinho Resende Assis

Institution
UP-FEUP

2020

Deteção de publicidade em conteúdos de televisão sem informação a priori

Author
Guilherme Dias Castro

Institution
UP-FEUP