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About

About

I was born in the district of Porto. I got a degree in Eletric and Computer Engeneering in 2001, a Master degre in Networks and Communication Services in 2004 and the PhD degree in Eletric and COmputer Engeneering in 2012, all from the Faculty of Engeneering of the University of Porto. I've been a collaborator of INESC TEC since 2001 and I'm currently a Senior Researcher at the Center of Telecommunications and Multimedia. I'm also an Invited Adjunct Professor at the School f Engeneering of the Polythecnic Institute of Porto. My current reseach interests include image and video processing, multimedia systems and computer vision. 

Interest
Topics
Details

Details

009
Publications

2019

Efficient CIEDE2000-based Color Similarity Decision for Computer Vision

Authors
Pereira, A; Carvalho, P; Coelho, G; Corte-Real, L;

Publication
IEEE Transactions on Circuits and Systems for Video Technology

Abstract

2019

Face Detection in Thermal Images with YOLOv3

Authors
Silva, G; Monteiro, R; Ferreira, A; Carvalho, P; Corte-Real, L;

Publication
Advances in Visual Computing - Lecture Notes in Computer Science

Abstract

2019

Stereo vision system for human motion analysis in a rehabilitation context

Authors
Matos, AC; Terroso, TA; Corte Real, L; Carvalho, P;

Publication
Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization

Abstract
The present demographic trends point to an increase in aged population and chronic diseases which symptoms can be alleviated through rehabilitation. The applicability of passive 3D reconstruction for motion tracking in a rehabilitation context was explored using a stereo camera. The camera was used to acquire depth and color information from which the 3D position of predefined joints was recovered based on: kinematic relationships, anthropometrically feasible lengths and temporal consistency. Finally, a set of quantitative measures were extracted to evaluate the performed rehabilitation exercises. Validation study using data provided by a marker based as ground-truth revealed that our proposal achieved errors within the range of state-of-the-art active markerless systems and visual evaluations done by physical therapists. The obtained results are promising and demonstrate that the developed methodology allows the analysis of human motion for a rehabilitation purpose. © 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group.

2018

BMOG: boosted Gaussian Mixture Model with controlled complexity for background subtraction

Authors
Martins, I; Carvalho, P; Corte Real, L; Alba Castro, JL;

Publication
Pattern Analysis and Applications

Abstract

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.

Supervised
thesis

2018

Optimizing customer response to direct marketing initiatives

Author
Francisco António Dias Amorim

Institution
UP-FEUP

2017

Image Processing for Event Detection in Retail Environments

Author
Pedro Daniel Nunes Querido

Institution
UP-FEUP

2015

People Re-identification in Multi-camera Environments

Author
Bruno Macedo Martins Santos Moreira

Institution
UP-FEUP

2015

Processamento de Vídeo para Promoção da Atividade Física

Author
Isaac José do Couto Lopes

Institution
UP-FEUP

2015

Seguimento de grupos de pessoas utilizando vídeo

Author
Alexandra Maria Pereira Familiar

Institution
UP-FEUP