Estimating Anthropometric Marker Locations from 3-D LADAR Point Clouds

An area of interest for improving the identification portion of the system is in extracting anthropometric markers from a Laser Detection and Ranging (LADAR) point cloud. Analyzing anthropometrics markers is a common means of studying how a human moves and has been shown to provide good results in determining certain demographic information about the subject. This research examines a marker extraction method utilizing principal component analysis (PCA), self-organizing maps (SOM), alpha hulls, and basic anthropometric knowledge. The performance of the extraction algorithm is tested by performing gender classification with the calculated markers

Génération et édition de textures géométriques représentées par des ensembles de points

Thèse numérisée par la Division de la gestion de documents et des archives de l'Université de Montréal

MULTISCALE SURFACE REPRESENTATION AND RENDERING FOR POINT CLOUDS

We introduce a new multiscale geometry representation based on tree-structured piecewise plane approximation of 3-D surface geometry. Dyadic division and plane approximation of points within each dyadic cube result in a tree-structured multiscale representation of the 3-D surface described by point cloud data. We then perform a complexity-regularized tree pruning to obtain a compact representation of the surface geometry. Based on its adaptivity and multiscale structure, the proposed representation scheme provides a desirable framework for efficient geometry modelling, fast processing, and geometry coding. We apply the proposed geometry models to point cloud rendering to demonstrate supremacy of our efficient geometry representation. 1