• 대한인간공학회:학술대회논문집
• /
• 대한인간공학회 1994년도 춘계학술대회논문집
• /
• pp.32-37
• /
• 1994

This paper surveys the various methodologies for the objective measurement of visual fatigue. Visual fatigue is a psychophysiological symtom caused by the excessive use of eyes and it can be used as an important measure of the effectiveness and the safety of visual displays. The purpose of this paper is to compare the various visual fatigue measurement methodologies in a sense of the suitability for the ergonomic research. The measurement methodologies based on accommodation, convergence, visual evoked potential, eye movement, eye blinking, and flicker fusion were discussed and compared.

• 한국정밀공학회지
• /
• 제16권8호
• /
• pp.113-121
• /
• 1999

It is necessary to calibrate measurement systems to enhance its measurement accuracy. The visual sensing system that is presented in our previous work has to be calibrated, too. It is a multiple mirror system for three-dimensional measurement, which is composed of a camera and a series of mirrors. It is important to calibrate the positions and orientations of the mirrors relative to the camera because they have direct influence on the relationship between the image plane and the task space. This paper presents the calibration method for the visual sensing system. To confirm the measurement performance of the implemented system. its measurement accuracy in measuring the locations in three-dimensional space is investigated. A series of experiments for measuring the locations of the circle-shaped marks are performed. Experimental results show that the sensing system can be effectively used for three-dimensional measurement.

• 대한인간공학회지
• /
• 제30권1호
• /
• pp.195-202
• /
• 2011

Objective: The aim of this study is to investigate and review the previous researches about objective measuring fatigue caused by visual stimuli. Also, we analyze possibility of alternative visual fatigue measurement methods using facial expression recognition and gesture recognition. Background: In most previous researches, visual fatigue is commonly measured by survey or interview based subjective method. However, the subjective evaluation methods can be affected by individual feeling's variation or other kinds of stimuli. To solve these problems, signal and image processing based visual fatigue measurement methods have been widely researched. Method: To analyze the signal and image processing based methods, we categorized previous works into three groups such as bio-signal, brainwave, and eye image based methods. Also, the possibility of adopting facial expression or gesture recognition to measure visual fatigue is analyzed. Results: Bio-signal and brainwave based methods have problems because they can be degraded by not only visual stimuli but also the other kinds of external stimuli caused by other sense organs. In eye image based methods, using only single feature such as blink frequency or pupil size also has problem because the single feature can be easily degraded by other kinds of emotions. Conclusion: Multi-modal measurement method is required by fusing several features which are extracted from the bio-signal and image. Also, alternative method using facial expression or gesture recognition can be considered. Application: The objective visual fatigue measurement method can be applied into the fields of quantitative and comparative measurement of visual fatigue of next generation display devices in terms of human factor.

• 국제학술발표논문집
• /
• The 10th International Conference on Construction Engineering and Project Management
• /
• pp.1019-1026
• /
• 2024

In the construction industry, there is a growing demand for improving productivity, and development of autonomous operation systems for construction machinery is progressing. Autonomous operation of construction machinery requires positioning information because construction must be carried out at planned locations. In this paper, we focused on Visual Simultaneous Localization and Mapping (Visual SLAM) as a method for obtaining location information for construction machinery and proposed an automated operation system using Visual SLAM. For automated driving, the indirect method based on ORB features is used in Visual SLAM, and processes such as mask processing for surrounding moving objects and measurement of initial positions using markers are performed. With the proposed system, it was confirmed that it is possible to perform automated operation in an experimental environment using the location information output by Visual SLAM. In addition, the experiment was conducted to verify the measurement accuracy when using Visual SLAM during construction work at actual construction sites. As a result, the measurement accuracy was less than 500 mm, which is a usable accuracy for actual construction. By using this system, it is possible to obtain the location information of construction machinery even in environments where GNSS cannot be used, and productivity at construction sites can be improved by performing automated operation.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2001년도 ICCAS
• /
• pp.88.3-88
• /
• 2001

In this paper, an on-line multi-sensor visual inspection technique for seamless steel pipe´s straightness is developed. The basic principle of the visual measuring method is detailed. The modeling of visual sensor, measurement system and data processing are presented. In order to test the accuracy of the multi-sensor visual inspection, an experiment inspecting the straightness of a 1500mm long seamless steel pipe is made. The experiment results show that the visual inspection technique can achieve on-line measurement and offers high precision and stability.

• 한국전문물리치료학회지
• /
• 제21권3호
• /
• pp.73-79
• /
• 2014

The purposes of the current study were to (1) estimate the inter-rater agreement for visual assessment of scapular downward rotation (SDR), (2) develop the scapular downward rotation index (SDRI) as a method to measure SDR objectively and quantitatively, and (3) analyze the intra- and inter-rater reliability of the SDRI. Twenty subjects with scapular downward rotation syndrome (SDRS) were recruited for this study. The visual assessment and the measurement for the SDRI were conducted by two examiners in two sessions each. The SDRI [$(a-b){\div}a{\times}100$] is calculated with the measurement of two linear distances: One is a perpendicular distance from the root of the scapular spine to the thoracic mid-line (a), and the other is a perpendicular distance from the inferior angle of the scapula to the thoracic mid-line (b). Cohen's kappa coefficient was calculated to estimate the inter-rater agreement for visual assessment. Intra-class correlation coefficients (ICCs) with a 95% confidence interval (CI), the standard error of measurement, and minimal detectable differences were calculated to assess intra- and inter-rater reliability of SDR measurement using the SDRI. The results indicated that the kappa coefficient of inter-rater agreement for visual assessment was fair (${\kappa}=.21$). The intra-rater reliability of SDR measurement using the SDRI was excellent for examiner 1 (ICC=.92, 95% CI=.78~.97) and good for examiner 2 (ICC=.82, 95% CI=.55~.93). The inter-rater reliability was moderate (ICC=.73, 95% CI=.32~.89). These findings showed that SDR measurement using the SDRI for subjects with SDRS may be considered reliable and better than the visual assessment.

• Journal of the Optical Society of Korea
• /
• 제16권2호
• /
• pp.145-150
• /
• 2012

We present a display-based visual stimulator for psychophysical and electrophysiological visual sensitivity measurements. The stimulator offers various psychophysical visual stimuli and transfers the signals from external devices along with the stimulation signals to an electrophysiological recorder. As an experimental demonstration, we perform a visual sensitivity experiment in the mesopic vision range by using the display-based stimulator. The intensity of the steady-state visual evoked potential is observed to correlate with the luminance of the flickering visual stimulation. For the psychophysically determined detection thresholds, we determine the mesopic luminance, showing agreement with the perceived brightness within the uncertainty of the luminance measurement.

• 한국정밀공학회:학술대회논문집
• /
• 한국정밀공학회 1996년도 춘계학술대회 논문집
• /
• pp.281-285
• /
• 1996

In this paper, I made visual inspection system using Vision Board and it is consist of an illuminator (a fluorescent lamp), image input device(CCD(Charge)Coupled Device) camera), image processing system(Vision Board(FARAMVB-02), image output device(videomonitor, printer), a measuring instrument(TELMN1000). Length measurement by visual inspection system is used 100mm gauge block instead of calculating distance between camera and object, it measured horizontal and vertical length factor from 400mm to 650mm by increasing 50mm. In this place, measured horizontal and vertical length factor made use of length measurement of a injection. A measuring instrument used to compare a measured length of a injection visual inspection system with it. In conclusion, length measurement of a injection compared a measuring instrument withvisual inspecion system using length factor of 100mm guage block. Maximum error of length compared two devices a measuring instrument with visual inspection system is 0.55mm. And operation program is made up Borland C++ 3.1. By changing, it is applied to various uses.

• 전기학회논문지
• /
• 제68권1호
• /
• pp.189-198
• /
• 2019

In recent years, visual-inertial odometry(VIO) algorithms have been extensively studied for the indoor/urban environments because it is more robust to dynamic scenes and environment changes. In this paper, we propose loosely coupled(LC) VIO algorithm that utilizes the velocity vectors from both visual odometry(VO) and inertial measurement unit(IMU) as a filter measurement of Extended Kalman filter. Our approach improves the estimation performance of a filter without adding extra sensors while maintaining simple integration framework, which treats VO as a black box. For the VO algorithm, we employed a fundamental part of the ORB-SLAM, which uses ORB features. We performed an outdoor experiment using an RGB-D camera to evaluate the accuracy of the presented algorithm. Also, we evaluated our algorithm with the public dataset to compare with other visual navigation systems.

• Smart Structures and Systems
• /
• 제30권3호
• /
• pp.287-301
• /
• 2022

The machine-vision based structural displacement measurement methods are widely used due to its flexible deployment and non-contact measurement characteristics. The accuracy of vision measurement is directly related to the image resolution. In the field of computer vision, super-resolution reconstruction is an emerging method to improve image resolution. Particularly, the deep-learning based image super-resolution methods have shown great potential for improving image resolution and thus the machine-vision based measurement. In this article, we firstly review the latest progress of several deep learning based super-resolution models, together with the public benchmark datasets and the performance evaluation index. Secondly, we construct a binocular visual measurement platform to measure the distances of the adjacent corners on a chessboard that is universally used as a target when measuring the structure displacement via machine-vision based approaches. And then, several typical deep learning based super resolution algorithms are employed to improve the visual measurement performance. Experimental results show that super-resolution reconstruction technology can improve the accuracy of distance measurement of adjacent corners. According to the experimental results, one can find that the measurement accuracy improvement of the super resolution algorithms is not consistent with the existing quantitative performance evaluation index. Lastly, the current challenges and future trends of super resolution algorithms for visual measurement applications are pointed out.