An efficient method for fully automatic 3D digitization of unknown objects

2013

Our goal is to develop a complete and automatic scanning strategy with minimum prior information about the object shape. We aim to establish a methodology for the automation of the 3D digitization process. The paper presents a novel approach to determine the Next Best View (NBV) for an efficient reconstruction of highly accurate 3D models. Our method is based on the classification of the acquired surfaces into Well Visible and Barely Visible combined with a best view selection algorithm based on mean shift, which avoids unreachable positions. Our approach is applicable to all kinds of range sensors. To prove the efficiency and the robustness of our method, test objects are first scanned man…

Trois algorithmes intelligents pour la numérisation 3D automatique d'objets inconnus

2013

National audience; Ce papier propose trois approches itératives et intelligentes de planification de vue pour la numérisation 3D d'objets sans connaissance a priori de leurs formes. La première méthode est une approche simple et naïve basée sur la génération d'un ensemble de points de vues par échantillonnage régulier de l'enveloppe englobante des données acquises. La deuxième méthode est basée sur une analyse de l'orientation des différentes parties acquises. La troisième méthode vise à explorer les parties de l'objet qui figurent dans la limite du champ de visibilité et est basée sur un couplage de la visibilité angulaire avec la visibilité réelle par lancer de rayons. Les résultats de nu…

PROCEDE DE NUMERISATION TRIDIMENSIONNELLE AUTOMATIQUE

2012

View planning algorithms for fully automatic 3D acquisition of unknown objects

2013

International audience; This paper addresses the view planning problem for the digitization of 3D objects without prior knowledge on their shape and presents a novel method called Orientation, Angle and Covering (OAC). The proposed method is based on a combination of two concepts: the Mass Vector Chains (MVC) and the Measurability Matrix. The MVC allows to define the global orientation of the scanned part. All of the view points are sorted using an orientation criterion to define a first set of candidates for the Next Best View (NBV). The Measurability Matrix allows to determine the coverage rate for each candidate. The covering criterion leads to reduce the number of view points of the fir…

View Planning Approach for Automatic 3D Digitization of Unknown Objects

2012

International audience; This paper addresses the view planning problem for the digitization of 3D objects without prior knowledge on their shape and presents a novel surface approach for the Next Best View (NBV) computation. The proposed method uses the concept of Mass Vector Chains (MVC) to define the global orientation of the scanned part. All of the viewpoints satisfying an orientation constraint are clustered using the Mean Shift technique to construct a first set of candidates for the NBV. Then, a weight is assigned to each mode according to the elementary orientations of its different descriptors. The NBV is chosen among the modes with the highest weights and which comply with the rob…