Luciano Silva

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This paper presents a novel automatic framework to perform 3D face recognition. The proposed method uses a simulated annealing-based approach (SA) for range image registration with the surface interpenetration measure (SIM), as similarity measure, in order to match two face images. The authentication score is obtained by combining the SIM values(More)
This paper addresses the range image registration problem for views having low overlap and which may include substantial noise. The current state of the art in range image registration is best represented by the well-known iterative closest point (ICP) algorithm and numerous variations on it. Although this method is effective in many domains, it(More)
We present a methodology for face segmentation and facial landmark detection in range images. Our goal was to develop an automatic process to be embedded in a face recognition system using only depth information as input. To this end, our segmentation approach combines edge detection, region clustering, and shape analysis to extract the face region, and our(More)
This paper presents a novel range image segmentation algorithm based on planar surface extraction. The algorithm was applied to common range image databases and was favorably compared against seven other segmentation algorithms using a popular evaluation framework. The experimental results show that, as compared to the other methods, our algorithm presents(More)
This paper presents our methodology for face and facial features detection to improve 3D face recognition in a presence of facial expression variation. Our goal was to develop an automatic process to be embedded in a face recognition system, using only range images as input. To do that, our approach combines traditional image segmentation techniques for(More)
This paper presents a novel range image segmentation method employing an improved robust estimator to iteratively detect and extract distinct planar and quadric surfaces. Our robust estimator extends M-estimator Sample Consensus/Random Sample Consensus (MSAC/RANSAC) to use local surface orientation information, enhancing the accuracy of inlier/outlier(More)
We present some results on newborn identification through high-resolution images of palmar surfaces. To our knowledge, there is no biometric system currently available that can be effectively used for newborn identification. The manual procedure of capturing inked footprints in practice for this purpose is limited for use inside hospitals and is not an(More)
In this article we propose a novel biometric identification method for newborn babies using their palmprints. A new high resolution optical sensor was developed, which obtains images with enough ridge minutiae to uniquely identify the baby. The palm and footprint images of 106 newborns were analysed, leading to the conclusion that palmprints yield more(More)