Performance-Enhanced Three-Dimensional Object Recognition by Computational Integral Imaging with Depth Data of Picked-Up Elemental Images

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概要

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• A highly performance-enhanced three-dimensional (3D) object recognition system has been implemented using a computational integral imaging technique with depth of picked-up elemental images. For this, depth data of the picked-up elemental images are extracted, and elemental images are classified into a number of groups depending on these depth values. Then, each group of depth-dependently classified elemental images is separately used for reconstructing the object image on each corresponding depth plane. By this method, defocused images resulting from the objects located on other depth planes, which unavoidably occur in the conventional computational integral imaging reconstruction (CIIR) method, can be effectively removed. That is, in the proposed method, only the clearly focused object images can be reconstructed where the objects were originally located. Thus, a significant performance improvement of the CIIR-based 3D object recognition system is obtained. Experimental results confirm the feasibility of the proposed method.

• Published by the Japan Society of Applied Physics through the Institute of Pure and Applied Physicsの論文
• 2009-09-25

著者

• Kim Eun-Soo

  3D Display Research Center, Department of Electronic Engineering, Kwangwoon University, 447-1 Wolge-dong, Nowon-gu, Seoul 139-701, Korea

• Li Gen

  3D Display Research Center, Department of Electronic Engineering, Kwangwoon University, 447-1 Wolge-dong, Nowon-gu, Seoul 139-701, Korea

• Kim Seung-Cheol

  3D Display Research Center, Department of Electronic Engineering, Kwangwoon University, 447-1 Wolge-dong, Nowon-gu, Seoul 139-701, Korea

関連論文

• Regularized Stereo Matching Scheme using Adaptive Disparity Estimation
• Computational Reconstruction of Three-Dimensional Objects in Integral Imaging using Lenslet Array
• Effective Depth Detection of Three-Dimensional Objects in Space with Picked-up and Computationally Reconstructed Integral Images
• Performance-Enhanced Three-Dimensional Object Recognition by Computational Integral Imaging with Depth Data of Picked-Up Elemental Images
• Parallax-Controllable Large-Depth Integral Imaging Scheme Using Lenslet Array
• Computational Depth Conversion of Reconstructed Three-Dimensional Object Images in Curving-Effective Integral Imaging System

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