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Correction of Missing Feature Points for 3D Modeling from 2D object images

2차원 객체 영상의 3차원 모델링을 위한 손실 특징점 보정

Koh, Sung-shik
고성식

  • Received : 2015.10.15
  • Accepted : 2015.11.09
  • Published : 2015.12.31

Abstract

How to recover from the multiple 2D images into 3D object has been widely studied in the field of computer vision. In order to improve the accuracy of the recovered 3D shape, it is more important that noise must be minimized and the number of image frames must be guaranteed. However, potential noise is implied when tracking feature points. And the number of image frames which is consisted of an observation matrix usually decrease because of tracking failure, occlusions, or low image resolution, and so on. Therefore, it is obviously essential that the number of image frames must be secured by recovering the missing feature points under noise. Thus, we propose the analytic approach which can control directly the error distance and orientation of missing feature point by the geometrical properties under noise distribution. The superiority of proposed method is demonstrated through experimental results for synthetic and real object.

Keywords

missing feature points;geometrical approach;SVD factorization;3D reconstruction

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