View Planning Approach for Automatic 3D Digitization of Unknown Objects

Abstract : 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.
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Conference papers
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https://hal.archives-ouvertes.fr/hal-00745605
Contributor : Souhaiel Khalfaoui <>
Submitted on : Thursday, October 25, 2012 - 10:07:01 PM
Last modification on : Friday, May 10, 2019 - 3:40:02 PM

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  • HAL Id : hal-00745605, version 1

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Souhaiel Khalfaoui, Ralph Seulin, Yohan Fougerolle, David Fofi. View Planning Approach for Automatic 3D Digitization of Unknown Objects. The QU3ST - 2.5D Sensing Technologies in Motion: The Quest for 3D, in conjunction with ECCV 2012, Oct 2012, Florence, Italy. pp.496-505. ⟨hal-00745605⟩

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