Three-Dimensional Object Reconstruction and Recognition Using Computational Integral Imaging and Statistical Pattern Analysis

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概要

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• In this paper, we discuss computational reconstruction and statistical pattern classification using integral imaging. Three-dimensional object information is numerically reconstructed at arbitrary depth-levels by averaging the corresponding pixels. The longitudinal distance and object boundary are estimated where the standard deviation of the intensity is minimized. Fisher linear discriminant analysis combined with principal component analysis is adopted for the classification of out-of-plane rotated objects. The Fisher linear discriminant analysis maximizes the class-discrimination while the principal component analysis minimizes the error between the original and the restored images. The presented method provides promising results for the distortion-tolerant pattern classification.

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

著者

• Son Jung-young

  Department Of Computer And Communication Engineering Daegu University

• Son Jung-Young

  Department of Computer and Communication Engineering, Daegu University, Gyeongsan, Gyeongbuk 712-714, Korea

• Yeom Seokwon

  Department of Computer and Communication Engineering, Daegu University, Gyeongsan, Gyeongbuk 712-714, Korea

• Kim Shin-Hwan

  Department of Computer and Communication Engineering, Daegu University, Gyeongsan, Gyeongbuk 712-714, Korea

• Lee Dongsu

  Department of Computer and Communication Engineering, Daegu University, Gyeongsan, Gyeongbuk 712-714, Korea

関連論文

• Comparisons of Perceived Images in Multiview and Integral Photography Based Three-Dimensional Imaging Systems
• Pixel Patterns for Voxels in Contact-Type Three Dimensional Imaging Systems
• Comparisons of Perceived Images in Multiview and Integral Photography Based Three-Dimensional Imaging Systems
• Three-Dimensional Object Reconstruction and Recognition Using Computational Integral Imaging and Statistical Pattern Analysis

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