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Your search keyword '"Nunes, Urbano"' showing total 26 results
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3. Enhancing Availability for Critical Services

Author

Gomes, Teresa, primary, Martins, Lúcia, additional, Girão-Silva, Rita, additional, Tipper, David, additional, Pašić, Alija, additional, Vass, Balázs, additional, Garrote, Luís, additional, Nunes, Urbano J, additional, Zachariasen, Martin, additional, and Rak, Jacek, additional

Published
2020
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11. Awareness of Road Scene Participants for Autonomous Driving

Author

Petrovskaya, Anna, primary, Perrollaz, Mathias, additional, Oliveira, Luciano, additional, Spinello, Luciano, additional, Triebel, Rudolph, additional, Makris, Alexandros, additional, Yoder, John-David, additional, Laugier, Christian, additional, Nunes, Urbano, additional, and Bessiere, Pierre, additional

Published
2012
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24. Camera Pose Estimation Using Images of Planar Mirror Reflections.

Author

Rodrigues, Rui, Barreto, João P., and Nunes, Urbano

Abstract

The image of a planar mirror reflection (IPMR) can be interpreted as a virtual view of the scene, acquired by a camera with a pose symmetric to the pose of the real camera with respect to the mirror plane. The epipolar geometry of virtual views associated with different IPMRs is well understood, and it is possible to recover the camera motion and perform 3D scene reconstruction by applying standard structure-from-motion methods that use image correspondences as input. In this article we address the problem of estimating the pose of the real camera, as well as the positions of the mirror plane, by assuming that the rigid motion between N virtual views induced by planar mirror reflections is known. The solution of this problem enables the registration of objects lying outside the camera field-of-view, which can have important applications in domains like non-overlapping camera network calibration and robot vision. We show that the positions of the mirror planes can be uniquely determined by solving a system of linear equations. This enables to estimate the pose of the real camera in a straightforward closed-form manner using a minimum of N = 3 virtual views. Both synthetic tests and real experiments show the superiority of our approach with respect to current state-of-the-art methods. [ABSTRACT FROM AUTHOR]

Published
2010
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25. Support Vector Machines and Features for Environment Perception in Mobile Robotics.

Author

Araújo, Rui, Nunes, Urbano, Oliveira, Luciano, Sousa, Pedro, and Peixoto, Paulo

Abstract

Environment perception is one of the most challenging and underlying task which allows a mobile robot to perceive obstacles, landmarks and extract useful information to navigate safely. In this sense, classification techniques applied to sensor data may enhance the way mobile robots sense their surroundings. Amongst several techniques to classify data and to extract relevant information from the environment, Support Vector Machines (SVM) have demonstrated promising results, being used in several practical approaches. This chapter presents the core theory of SVM, and applications in two different scopes: using Lidar (Light Detection and Ranging) to label specific places, and vision-based human detection aided by Lidar. [ABSTRACT FROM AUTHOR]

Published
2008
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