Variation in object shape is an important visual cue for deformable object recognition and classification. In this paper, we present an approach to model gradual changes in the ?-...
In this paper, we propose a novel boosted mixture learning (BML) framework for Gaussian mixture HMMs in speech recognition. BML is an incremental method to learn mixture models fo...
The state-of-the-art object detection algorithm learns a binary classifier to differentiate the foreground object from the background. Since the detection algorithm exhaustively s...
It was recently proposed the use of Bayesian networks for object tracking. Bayesian networks allow to model the interaction among detected trajectories, in order to obtain a relia...
Arnaldo J. Abrantes, Jorge S. Marques, Pedro Mende...
This paper presents an approach to endow a humanoid robot with the capability of learning new objects and recognizing them in an unstructured environment. New objects are learnt, w...
Dario Figueira, Manuel Lopes, Rodrigo M. M. Ventur...