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- Driving simulator for performance monitoring with physiological sensorsPublication . Raimundo, Diogo; Lourenço, André; Abrantes, ArnaldoThis paper describes a driving monitoring system based on a car driving simulator, specifically built for this project, using inexpensive off-the-shelf game technology (software and hardware). The project aims to study the effect of drowsiness (caused by fatigue, alcohol consumption, etc.) in driving performance and how it can be detected in advance in order to mitigate accidents. To achieve this, the system is continuously monitoring driver's physiological signals (e.g., heart rate) as well as her/his driving behavior. Electrocardiography (ECG) signal plays a central role in this project, since a feature derived from it - the HRV (Heart Rate Variability), more concretely its power spectral distribution - is used to continuously estimate the driver's degree of awareness and therefore for generation of alarms. A preliminary evaluation of the proposed system is discussed through the presentation of some experimental results.
- Methods for automatic and assisted image annotationPublication . Jesus, Rui; Abrantes, Arnaldo; Correia, NunoPersonal memories composed of digital pictures are very popular at the moment. To retrieve these media items annotation is required. During the last years, several approaches have been proposed in order to overcome the image annotation problem. This paper presents our proposals to address this problem. Automatic and semi-automatic learning methods for semantic concepts are presented. The automatic method is based on semantic concepts estimated using visual content, context metadata and audio information. The semi-automatic method is based on results provided by a computer game. The paper describes our proposals and presents their evaluations.
- Integrated vehicle classification systemPublication . Ferreira, Pedro Miguel; Jorge, Pedro; Marques, Gonçalo; Abrantes, Arnaldo; Amador, AntónioThis paper presents an integrated system for vehicle classification. This system aims to classify vehicles using different approaches: 1) based on the height of the first axle and_the number of axles; 2) based on volumetric measurements and; 3) based on features extracted from the captured image of the vehicle. The system uses a laser sensor for measurements and a set of image analysis algorithms to compute some visual features. By combining different classification methods, it is shown that the system improves its accuracy and robustness, enabling its usage in more difficult environments satisfying the proposed requirements established by the Portuguese motorway contractor BRISA.