6533b872fe1ef96bd12d2ef3

RESEARCH PRODUCT

View Planning Approach for Automatic 3D Digitization of Unknown Objects

Souhaiel KhalfaouiDavid FofiRalph SeulinYohan Fougerolle

subject

business.industryOrientation (computer vision)Computer science[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]02 engineering and technology[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Constraint (information theory)Set (abstract data type)[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]020204 information systems0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingComputer visionArtificial intelligenceMean-shiftbusinessDigitization

description

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 robotics constraints. Eventually, our method is generic since it is applicable to all kinds of scanners. Experiments applying a digitization cell demonstrate the feasibility and the efficiency of the approach which leads to an intuitive and fast 3D acquisition while moving efficiently the ranging device.

https://hal.archives-ouvertes.fr/hal-00745605