An approach of system calibration for UAV photogrammetry

2011 ◽  
Author(s):  
Ping Liu ◽  
Xi Chen ◽  
Liao Yang
Keyword(s):  
System Calibration

scholarly journals The DLR Spaceborne SAR Calibration Center

Frequenz ◽  
2017 ◽  
Vol 71 (11-12) ◽  
Author(s):  
Jens Reimann ◽  
Marco Schwerdt ◽  
Kersten Schmidt ◽  
Nuria Tous Ramon ◽  
Björn Döring
Keyword(s):  
Sar Image ◽  
Extensive Experience ◽  
System Calibration ◽  
Radar Measurements

AbstractA necessary activity for any SAR system is its calibration to establish the relation between radar measurements and geophysical parameters. During this process, all essential parameters of a SAR image are linked to their geophysical quantities. This includes the geolocation of the SAR image, its backscattering characteristics (in amplitude and in phase) and polarimetric information. The Microwaves and Radar Institute of the DLR has gained extensive experience in these calibration procedures during the last decades and has developed special methods and dedicated reference targets for spaceborne SAR system calibration. Through examples of calibration results obtained for different spaceborne SAR mission, the capabilities of the DLR SAR Calibration Center are presented.

Playing With BEARS: Balancing Effort, Accuracy, and Response Speed in a Semantic Feature Verification Anomia Treatment Game

2021 ◽  
pp. 1-27
Author(s):  
William S. Evans ◽  
Robert Cavanaugh ◽  
Yina Quique ◽  
Emily Boss ◽  
Jeffrey J. Starns ◽  
...  
Keyword(s):  
Treatment Outcomes ◽  
Retrieval Practice ◽  
Single Case ◽  
Case Series ◽  
Response Speed ◽  
Semantic Feature ◽  
System Calibration ◽  
Trade Offs ◽  
Practice Efficiency ◽  
Speed Accuracy

Purpose The purpose of this study was to develop and pilot a novel treatment framework called BEARS (Balancing Effort, Accuracy, and Response Speed). People with aphasia (PWA) have been shown to maladaptively balance speed and accuracy during language tasks. BEARS is designed to train PWA to balance speed–accuracy trade-offs and improve system calibration (i.e., to adaptively match system use with its current capability), which was hypothesized to improve treatment outcomes by maximizing retrieval practice and minimizing error learning. In this study, BEARS was applied in the context of a semantically oriented anomia treatment based on semantic feature verification (SFV). Method Nine PWA received 25 hr of treatment in a multiple-baseline single-case series design. BEARS + SFV combined computer-based SFV with clinician-provided BEARS metacognitive training. Naming probe accuracy, efficiency, and proportion of “pass” responses on inaccurate trials were analyzed using Bayesian generalized linear mixed-effects models. Generalization to discourse and correlations between practice efficiency and treatment outcomes were also assessed. Results Participants improved on naming probe accuracy and efficiency of treated and untreated items, although untreated item gains could not be distinguished from the effects of repeated exposure. There were no improvements on discourse performance, but participants demonstrated improved system calibration based on their performance on inaccurate treatment trials, with an increasing proportion of “pass” responses compared to paraphasia or timeout nonresponses. In addition, levels of practice efficiency during treatment were positively correlated with treatment outcomes, suggesting that improved practice efficiency promoted greater treatment generalization and improved naming efficiency. Conclusions BEARS is a promising, theoretically motivated treatment framework for addressing the interplay between effort, accuracy, and processing speed in aphasia. This study establishes the feasibility of BEARS + SFV and provides preliminary evidence for its efficacy. This study highlights the importance of considering processing efficiency in anomia treatment, in addition to performance accuracy. Supplemental Material https://doi.org/10.23641/asha.14935812

Complete Online Algorithm for Air Data System Calibration

2019 ◽  
Vol 56 (2) ◽  
pp. 517-528 ◽  
Author(s):  
Juan D. Jurado ◽  
Clark C. McGehee
Keyword(s):  
Online Algorithm ◽  
Data System ◽  
System Calibration

scholarly journals Registration Error Analysis for Augmented Reality

1997 ◽  
Vol 6 (4) ◽  
pp. 413-432 ◽  
Author(s):  
Richard L. Holloway
Keyword(s):  
Augmented Reality ◽  
Error Analysis ◽  
Optical Distortion ◽  
Calibration Error ◽  
Head Tracking ◽  
System Delay ◽  
System Calibration ◽  
The Real ◽  
Registration Error ◽  
Real Environment

Augmented reality (AR) systems typically use see-through head-mounted displays (STHMDs) to superimpose images of computer-generated objects onto the user's view of the real environment in order to augment it with additional information. The main failing of current AR systems is that the virtual objects displayed in the STHMD appear in the wrong position relative to the real environment. This registration error has many causes: system delay, tracker error, calibration error, optical distortion, and misalignment of the model, to name only a few. Although some work has been done in the area of system calibration and error correction, very little work has been done on characterizing the nature and sensitivity of the errors that cause misregistration in AR systems. This paper presents the main results of an end-to-end error analysis of an optical STHMD-based tool for surgery planning. The analysis was done with a mathematical model of the system and the main results were checked by taking measurements on a real system under controlled circumstances. The model makes it possible to analyze the sensitivity of the system-registration error to errors in each part of the system. The major results of the analysis are: (1) Even for moderate head velocities, system delay causes more registration error than all other sources combined; (2) eye tracking is probably not necessary; (3) tracker error is a significant problem both in head tracking and in system calibration; (4) the World (or reference) coordinate system adds error and should be omitted when possible; (5) computational correction of optical distortion may introduce more delay-induced registration error than the distortion error it corrects, and (6) there are many small error sources that will make submillimeter registration almost impossible in an optical STHMD system without feedback. Although this model was developed for optical STHMDs for surgical planning, many of the results apply to other HMDs as well.

scholarly journals Method for large-range structured light system calibration

2016 ◽  
Vol 55 (33) ◽  
pp. 9563 ◽  
Author(s):  
Yatong An ◽  
Tyler Bell ◽  
Beiwen Li ◽  
Jing Xu ◽  
Song Zhang
Keyword(s):  
Large Range ◽  
Structured Light ◽  
System Calibration ◽  
Light System ◽  
Structured Light System
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