3D Reconstruction of Dynamic Vehicles using Sparse 3D-Laser-Scanner and 2D Image FusionReport as inadecuate

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* Corresponding author 1 Gunadarma University 2 Le2i - Laboratoire Electronique, Informatique et Image

Abstract : Map building becomes one of the most interesting research topic in computer vision field nowadays. To acquire accurate large 3D scene reconstructions, 3D laser scanners are recently developed and widely used. They produce accurate but sparse 3D point clouds of the environments. However, 3D reconstruction of rigidly moving objects along side with the large-scale 3D scene reconstruction is still lack of interest in many researches. To achieve a detailed object-level 3D reconstruction, a single scan of point cloud is insufficient due to their sparsity. For example, traditional Iterative Closest Point ICP registration technique or its variances are not accurate and robust enough to registered the point clouds, as they are easily trapped into the local minima. In this paper, we propose an 3-Point RANSAC with ICP refinement algorithm to build 3D reconstruction of rigidly moving objects, such as vehicles, using 2D-3D camera setup. Results show that the proposed algorithm can robustly and accurately registered the sparse 3D point cloud.

Keywords : Registration 2D camera 3D camera 3D Reconstruction Point Cloud ICP

Author: Dennis Christie - Cansen Jiang - Danda Paudel - Cédric Demonceaux -

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


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