Paper Info
Title
A Generic Algorithm for Position-Orientation Estimation With Microscopic Vision
Abstract
Position and orientation (PO) estimation with microscopic vision is essential for various micromanipulation tasks. Herein, to improve the accuracy and flexibility of PO estimation, a generic algorithm is proposed based on discriminative correlation filter (DCF), in which a position-estimator and an orientation-estimator are combined into one framework with the developed mutual correction mechanism. The extraction of spectral features is utilized to decouple the rotation and translation transformations of target. And DCF is employed to rapidly estimate the orientation. In addition, the continuous convolution operator is implemented to obtain suhgrid resolution in the position-estimator. At last, both the stability and the accuracy of PO estimation are verified. The noise fluctuation in response distribution is effectively restrained to improve the robustness by the mutual correction mechanism. And the introduction of continuous convolution operation can improve the accuracy of position estimation too. The position error of similar to 1.00 mu m and the orientation error of similar to 1.20 degrees are achieved. The comparison and application experiments validate the comprehensive performance of algorithm. Its advantages include the high accuracy, the strong robustness to rotating influence, the universality for various microfeatures.
Year
DOI
Venue
2022
10.1109/TIM.2022.3176893
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
Keywords
DocType
Volume
Continuous convolution, discriminative correlation filter (DCF), microscopic vision, mutual correction mechanism, position and orientation (PO) estimation
Journal
71
ISSN
Citations 
PageRank 
0018-9456
0
0.34
References 
Authors
0
7
Name
Order
Citations
PageRank
Zheng Xu100.34
Gang Han200.34
Hongyu Du300.34
Xiaodong Wang400.68
Yanqi Wang500.34
Junshan Liu600.68
Yifan Yang700.34