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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

005
Publications

2018

GymApp: A real time physical activity trainner on wearable devices

Authors
Viana, P; Ferreira, T; Castro, L; Soares, M; Pinto, JP; Andrade, T; Carvalho, P;

Publication
Proceedings - 2018 11th International Conference on Human System Interaction, HSI 2018

Abstract
Technological advances are pushing into the mass market innovative wearable devices featuring increasing processing and sensing capacity, non-intrusiveness and ubiquitous use. Sensors built-in those devices, enable acquiring different types of data and by taking advantage of the available processing power, it is possible to run intelligent applications that process the sensed data to offer added-value to the user in multiple domains. Although not new to the modern society, it is unquestionable that the present exercise boom is rapidly spreading across all age groups. However, in a great majority of cases, people perform their physical activity on their own, either due to time or budget constraints and may easily get discouraged if they do not see results or perform exercises inadequately. This paper presents an application, running on a wearable device, aiming at operating as a personal trainer that validates a set of proposed exercises in a sports session. The developed solution uses inertial sensors of an Android Wear smartwatch and, based on a set of pattern recognition algorithms, detects the rate of success in the execution of a planned workout. The fact that all processing can be executed on the device is a differentiator factor to other existing solutions. © 2018 IEEE.

2017

A Hybrid Approach for Personalized News Recommendation in a Mobility Scenario Using Long-Short User Interest

Authors
Viana, P; Soares, M;

Publication
INTERNATIONAL JOURNAL ON ARTIFICIAL INTELLIGENCE TOOLS

Abstract
Access to information has been made easier in different domains that range from multimedia content, books, music, news, etc. To deal with the huge amount of alternatives, recommendation systems have been often used as a solution to filter the options and provide suggestions of items that might be of interest to an user. The news domain introduces additional challenges due not only to the large amount of new items produced daily but also due to their ephemeral timelife. In this paper, a news recommendation system which combines content-based and georeferenced techniques in a mobility scenario, is proposed. Taking into account the volatility of the information, short-term and long-term user profiles are considered and implicitly built. Besides tracking users' clicks, the system infers different levels of interest an article has by tracking and weighting each action in the system and in social networks. Impact of the different fields that make up a news is also taken into account by following the inverted pyramid model that assumes different levels of importance to each paragraph of the article. The solution was tested with a population of volunteers and results indicate that the quality of the recommendation approach is acknowledged by the users.

2017

A collaborative approach for semantic time-based video annotation using gamification

Authors
Viana, P; Pinto, JP;

Publication
HUMAN-CENTRIC COMPUTING AND INFORMATION SCIENCES

Abstract
Efficient access to large scale video assets, may it be our life memories in our hard drive or a broadcaster archive which the company is eager to sell, requires content to be conveniently annotated. Manually annotating video content is, however, an intellectually expensive and time-consuming process. In this paper we argue that crowdsourcing, an approach that relies on a remote task force to perform activities that are costly or time-consuming using traditional methods, is a suitable alternative and we describe a solution based on gamification mechanisms for collaboratively collecting timed metadata. Tags introduced by registered players are validated based on a collaborative scoring mechanism that excludes erratic annotations. Voting mechanisms, enabling users to approve or refuse existing tags, provide an extra guarantee on the quality of the annotations. The sense of community is also created as users may watch the crowd's favourite moments of the video provided by a summarization functionality. The system was tested with a pool of volunteers in order to evaluate the quality of the contributions. The results suggest that crowdsourced annotation can describe objects, persons, places, etc. correctly, as well as be very accurate in time.

2017

The semantics of movie metadata: Enhancing user profiling for hybrid recommendation

Authors
Soares, M; Viana, P;

Publication
Advances in Intelligent Systems and Computing

Abstract
In movie/TV collaborative recommendation approaches, ratings users gave to already visited content are often used as the only input to build profiles. However, users might have rated equally the same movie but due to different reasons: either because of its genre, the crew or the director. In such cases, this rating is insufficient to represent in detail users’ preferences and it is wrong to conclude that they share similar tastes. The work presented in this paper tries to solve this ambiguity by exploiting hidden semantics in metadata elements. The influence of each of the standard description elements (actors, directors and genre) in representing user’s preferences is analyzed. Simulations were conducted using Movielens and Netflix datasets and different evaluation metrics were considered. The results demonstrate that the implemented approach yields significant advantages both in terms of improving performance, as well as in dealing with common limitations of standard collaborative algorithm. © Springer International Publishing AG 2017.

2016

A hybrid recommendation system for news in a mobile environment

Authors
Viana, P; Soares, M;

Publication
ACM International Conference Proceeding Series

Abstract
Over the last few years consumption of news articles has shifted more and more from the written versions towards the web. Mobile devices, which became more powerful, with larger screens and connected to the Internet, have had a great influence on this paradigm change. A critical problem associated to online news is related to the fact that the large number of daily articles can be overwhelming to the users. Recommendation services can largely improve the efficiency and accuracy of acquired information. These systems are designed to filter critical news, key events and meaningful items that might be of interest to a reader. In this paper, a news recommendation system in a mobility scenario is presented. The implemented recommendation system combines content-based and georeferenced recommendation techniques. Recommendations are supported by short-term and long-term user profiles created implicitly and considering also the mobile device geolocation. The final recommendation list is obtained by combining recommendations provided by the different recommendation approaches. To evaluate the performance of the solution, a user study was conducted. Results indicate that the quality of the recommendations is acknowledged by the test users. The system was integrated in a mobile application of a Portuguese newspaper (Público) in the context of the project Pglobal. © 2016 ACM.

Supervised
thesis

2017

Anotação em conteúdos audiovisuais em contexto educativo

Author
João Miguel Calisto Marçal

Institution
UP-FEUP

2017

ANALYSIS AND TESTING METHODOLOGY FOR BLUETOOTH AUDIO IN 0KM/FIELD CLAIMED PRODUCTS OF BOSCH CAR MULTIMEDIA PORTUGAL, S.A.

Author
ARAVIND MARIMUTHU

Institution
IPP-ISEP

2017

SINGLE SIGN-ON E USER EXPERIENCE DO IPORTALDOC

Author
MIGUEL ÂNGELO DA COSTA SANTOS

Institution
IPP-ISEP

2017

ALGORITMOS CRIPTOGRÁFICOS E O SEU DESEMPENHO NO ARDUINO

Author
NUNO JOSÉ TEIXEIRA REIS BARBOSA

Institution
IPP-ISEP

2016

Reconhecimento de Exercícios Físicos em Tempo-Real em Dispositivos Wearable

Author
TIAGO MIGUEL DA SILVA FERREIRA

Institution
IPP-ISEP