Urbano Nunes

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This work proposes a novel classifier-fusion scheme using learning algorithms, i.e. syntactic models, instead of the usual Bayesian or heuristic rules. Moreover, this paper complements the previous comparative studies on DaimlerChrysler Automotive Dataset, offering a set of complementary experiments using feature extractor and classifier combinations. The(More)
Why is pedestrian detection still very challenging in realistic scenes? How much would a successful solution to monocular depth inference aid pedestrian detection? In order to answer these questions we trained a state-of-the-art deformable parts detector using different configurations of optical images and their associated 3D point clouds, in conjunction(More)
A feature detection system has been developed for real-time identification of lines, circles and people legs from laser range data. A new method suitable for arc/circle detection is proposed: the Inscribed Angle Variance (IAV). Lines are detected using a recursive line fitting method. The people leg detection is based on geometrical relations. The system(More)
This paper presents a new algorithm for the extrinsic calibration of a perspective camera and an invisible 2D laser-rangefinder (LRF). The calibration is achieved by freely moving a checkerboard pattern in order to obtain plane poses in camera coordinates and depth readings in the LRF reference frame. The problem of estimating the rigid displacement between(More)
This paper presents, in detail, the implementation of a new control strategy, Kalman-based active observer controller (AOB), for the path following of wheeled mobile robots (WMRs) subject to nonholonomic constraints. This control strategy presents some particularities as being used in discrete mode, and being robust against uncertainties and disturbances(More)
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(More)
This paper proposes three novel training methods, two of them based on the backpropagation approach and a third one based on information theory for multilayer perceptron (MLP) binary classifiers. Both backpropagation methods are based on the maximal-margin (MM) principle. The first one, based on the gradient descent with adaptive learning rate algorithm(More)
An approach to increase road capacity consists in making vehicles move much closer to each other, i.e. using platoons, and to avoid the constant stop-and-go in urban traffic. This paper addresses the studies of new models to allow the research of cooperative and autonomous communication-enabled vehicles, with platooning capabilities, and the addition of new(More)
In this work, we propose an approach that relies on cues from depth perception from RGB-D images, where features related to human body motion (3D skeleton features) are used on multiple learning classifiers in order to recognize human activities on a benchmark dataset. A Dynamic Bayesian Mixture Model (DBMM) is designed to combine multiple classifier(More)