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

Autor:	Zhan-Li Sun, Zhi-Gang Zeng, Kin-Man Lam, Jia-Xiang Wang, Xia Chen
Rok vydání:	2019
Předmět:	Set (abstract data type) Rank (linear algebra) Computer science Applied Mathematics Signal Processing Frame (networking) Trajectory Estimator Structure from motion Electrical and Electronic Engineering Algorithm Image (mathematics)
Zdroj:	IEEE Signal Processing Letters. 26:1808-1811
ISSN:	1558-2361 1070-9908
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::96188aa0c83492536bbd945ea4aa6720 https://doi.org/10.1109/lsp.2019.2950594 Zobrazit plný text záznamu