A CSF-Based CNR Approach for Small-Size Image Sequences

Jia Xiang Wang, Zhan Li Sun, Xia Chen, Kin Man Lam, Zhi Gang Zeng

Research output: Journal article publicationJournal articleAcademic researchpeer-review

Abstract

For non-rigid structure from motion (NRSFM), the performance of most traditional approaches may decrease significantly when the frame number of the image sequence is relatively small. In this letter, a column space fitting (CSF) based consensus of non-rigid (CNR) reconstruction approach is proposed to deal with the 3D structure estimation problem for small-size image sequences. In the proposed method, a set of trajectory groups are first extracted by utilizing the distance weight of the pairwise points. In order to improve the estimation accuracy, an adaptive rank selection strategy is designed to choose the approximately optimal rank parameter. Corresponding to the trajectory group, the z-coordinates of the observation matrix are estimated by the CSF algorithm due to its good performance. After obtaining the outputs of the CSF-based weak estimators, the final 3D shape is derived by combining the outputs via the alternating directional method of multipliers. Experimental results on several widely used image sequences demonstrate the effectiveness and feasibility of the proposed algorithm.

Original languageEnglish
Article number8889394
Pages (from-to)1808-1811
Number of pages4
JournalIEEE Signal Processing Letters
Volume26
Issue number12
DOIs
Publication statusPublished - Dec 2019

Keywords

  • column space fitting
  • consensus of non-rigid reconstruction
  • Non-rigid structure from motion

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering
  • Applied Mathematics

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