Computer Vision and Robotics for Cultural Heritage: Theory and Applications.

Computer vision and robotics are more and more involved in cultural heritage [...

Automatic face segmentation and facial landmark detection in range images.

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 landmark detection approach combines surface curvature information and depth relief curves to find the nose and eye landmarks.

Using computer vision to help the determination of the gestational age of newborns.

Rationale And Objectives: This report presents a computational approach to help the gestational age determination of newborns. Gestational age knowledge is fundamental to guide postnatal treatment and increase survival chances of newborns. However, current methods are invasive and do not generate precise results, mainly because they were developed based on nonpremature populations.

Range image segmentation into planar and quadric surfaces using an improved robust estimator and genetic algorithm.

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 classification when processing noisy range data describing multiple structures. An efficient approximation to the true geometric distance between a point and a quadric surface also contributes to effectively reject weak surface hypotheses and avoid the extraction of false surface components.