Dataset Information

Calibration tools for PC-based vision assessment.

ABSTRACT: This paper details the research and development of the PC Vision system, a unique calibration and monitoring subsystem that will enable use of personal computers as accurately calibrated and controlled vision test instruments. The need for such a system is evident. Display intensity and chromaticity, test distance, room illumination, and a number of other variables must be controlled to avoid unexplained discrepancies in test outcomes, within and between individuals and test locations. Modern displays (CRT-, LCD-, or projector-based) have sufficient resolution, gamut, and stability to allow high-quality stimulus presentation. The PC Vision system consists of two categorical functions - one to calibrate screen properties, the other to monitor room and test setup conditions - packaged into a fully integrated hardware prototype.

SUBMITTER: Rolkosky DJ

PROVIDER: S-EPMC3897264 | biostudies-other | 2009

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

Calibration tools for PC-based vision assessment.

Rolkosky David J DJ Dagnelie Gislin G Kramer Kevin K Havey Gary G Seifert Gregory J GJ

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 20090101

This paper details the research and development of the PC Vision system, a unique calibration and monitoring subsystem that will enable use of personal computers as accurately calibrated and controlled vision test instruments. The need for such a system is evident. Display intensity and chromaticity, test distance, room illumination, and a number of other variables must be controlled to avoid unexplained discrepancies in test outcomes, within and between individuals and test locations. Modern di ...[more]

PMID: 19964242

Similar Datasets

Project description:There is no generally accepted medical or surgical treatment to stop the progressive course of retinitis pigmentosa. Previous studies have suggested lutein as a potential treatment with positive effects on macular pigment density. The objective of this study was to examine the effect of lutein supplementation on preservation of visual function in patients with retinitis pigmentosa (RP) METHODS: In a double-masked randomized placebo-controlled phase I/II clinical trial with a cross-over design, 34 adult patients with RP were randomized to two groups. One group, consisted of 16 participants, received lutein supplementation (10 mg/d for 12 wks followed by 30 mg/d) for the first 24 weeks and then placebo for the following 24 weeks, while the other group included 18 participants for whom placebo (24 weeks) was administered prior to lutein. Visual acuity, contrast sensitivity, and central visual field were measured at different illumination levels at baseline and every week using a PC-based test at home.For visual acuity (VA) at normal illumination level, treatment with lutein reduced logMAR, i.e. improved VA, but this effect was not statistically significant. The changes in normal (100%), low (4%), and very low (0.1%) illumination log CS were not statistically significant (p-values: 0.34, 0.23, and 0.32, respectively). Lutein had a statistically significant effect on visual field (p-value: 0.038) and this effect increased in the model assuming a 6-week delay in effect of lutein. Comparing the development of vision measures against the natural loss expected to occur over the course of 48 weeks, most measures showed reduced decline, and these reductions were significant for normal illumination VA and CS.These results suggest that lutein supplementation improves visual field and also might improve visual acuity slightly, although these results should be interpreted cautiously. As a combined phase I and II clinical trial, this study demonstrated the efficacy and safety of lutein supplementation.

Project description:Hand-eye calibration is an important step in controlling a vision-guided robot in applications like part assembly, bin picking and inspection operations etc. Many methods for estimating hand-eye transformations have been proposed in literature with varying degrees of complexity and accuracy. However, the success of a vision-guided application is highly impacted by the accuracy the hand-eye calibration of the vision system with the robot. The level of this accuracy depends on several factors such as rotation and translation noise, rotation and translation motion range that must be considered during calibration. Previous studies and benchmarking of the proposed algorithms have largely been focused on the combined effect of rotation and translation noise. This study provides insight on the impact of rotation and translation noise acting in isolation on the hand-eye calibration accuracy. This deviates from the most common method of assessing hand-eye calibration accuracy based on pose noise (combined rotation and translation noise). We also evaluated the impact of the robot motion range used during the hand-eye calibration operation which is rarely considered. We provide quantitative evaluation of our study using six commonly used algorithms from an implementation perspective. We comparatively analyse the performance of these algorithms through simulation case studies and experimental validation using the Universal Robot's UR5e physical robots. Our results show that these different algorithms perform differently when the noise conditions vary rather than following a general trend. For example, the simultaneous methods are more resistant to rotation noise, whereas the separate methods are better at dealing with translation noise. Additionally, while increasing the robot rotation motion span during calibration enhances the accuracy of the separate methods, it has a negative effect on the simultaneous methods. Conversely, increasing the translation motion range improves the accuracy of simultaneous methods but degrades the accuracy of the separate methods. These findings suggest that those conditions should be considered when benchmarking algorithms or performing a calibration process for enhanced accuracy.

Dataset Information

Calibration tools for PC-based vision assessment.

Publications

Calibration tools for PC-based vision assessment.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets