• Journal of the Ergonomics Society of Korea
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• v.28 no.3
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• pp.55-62
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• 2009

This study is concerned with predicting human search performance using a visual lobe. The most previous studies on human performance in visual search have been limited to a single-target search. This study extended the visual search research to multiple-target search including targets of different types as well as targets of same types. A model for predicting visual search performance was proposed and the model was validated by human search data. Additionally, this study found that human subjects always did not use a constant ratio of the whole visual lobe size for each type of targets in visual search process. The more conspicuous the target is, the more ratio of the whole visual lobe size human subjects use. The model that can predict human performance in multiple-target search may facilitate visual inspection plan in manufacturing.

• Journal of Korean Institute of Industrial Engineers
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• v.27 no.2
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• pp.190-196
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• 2001

This study aims to develop three types of the visual fields: stationary field, eye field, and head field, which are classified depending upon the eye and head movements. A visual experiment taking target size, target color, and meridian into account was conducted, in which the L32 orthogonal array was employed. The results showed that target size and meridian were significant at ${\alpha}$=0.01 in all three visual fields. Contrary to expectation, target color was significant at ${\alpha}$=0.10 only in the head field. Furthermore, the differences in size of the head field depending upon four target colors were negligibly small. Three linear regression models were provided to generate visual fields which are appropriate for given visual task's characteristics. In addition, a simple method using adjusting factor was also proposed so that anyone without knowledge for human factors/ergonomics can easily generate and use them when designing or evaluating visual tasks. It is expected that the visual fields presented in this study can be easily used even by non-ergonomic experts in real situations due to their simplicity.

• Science of Emotion and Sensibility
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• v.13 no.3
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• pp.475-484
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• 2010

This study examined the influence of the SOA(stimulus onset asynchrony) between visual and auditory stimuli on the integration phenomenon of audio-visual senses. Within the stimulus integration phenomenon, the redundant target effect (the faster and more accurate response to the target stimulus when the target stimulus is presented with more than two modalities) and the visual dominance effect (the faster and more accurate response to a visual stimulus compared to an auditory stimulus) were examined as we composed a visual and auditory unimodal target condition and a multimodal target condition and then observed the response time and accuracy. Consequently, despite the change between visual and auditory stimuli SOA, there was no redundant target effect present. The auditory dominance effect appeared when the SOA between the two stimuli was over 100ms. Theses results imply that the redundant target effect is continuously maintained even when the SOA between two modal stimuli is altered, and also suggests that the behavioral results of superior information processing can only be deducted when the time difference between the onset of the auditory stimuli and the visual stimuli is approximately over 100ms.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.6
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• pp.1245-1254
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• 2011

This paper proposes a target tracking algorithm for wheeled mobile robots using in various fields. For the stable tracking, we apply a vision system to a mobile robot which can extract targets through image processing algorithms. Furthermore, this paper presents an algorithm to position the mobile robot at the desired location from the target by estimating its relative position and attitude. We show the problem in the tracking method using the Position-Based Visual Servo(PBVS) control, and propose a tracking method, which can achieve the stable tracking performance by combining the PBVS control with Image-Based Visual Servo(IBVS) control. When the target is located around the outskirt of the camera image, the target can disappear from the field of view. Thus the proposed algorithm combines the control inputs with of the hyperbolic form the switching function to solve this problem. Through both simulations and experiments for the mobile robot we have confirmed that the proposed visual servo control method is able to enhance the stability compared to of the method using only either PBVS or IBVS control method.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.12
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• pp.1033-1041
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• 2003

A new visual tracking scheme is proposed for a mobile robot that tracks a moving object in 3D space in real time. Visual tracking is to control a mobile robot to keep a moving target at the center of input image at all time. We made it possible by simplifying the relationship between the 2D image frame captured by a single camera and the 3D workspace frame. To precisely calculate the input vector (orientation and distance) of the mobile robot, the speed vector of the target is determined by eliminating the speed component caused by the camera motion from the speed vector appeared in the input image. The problem of temporary disappearance of the target form the input image is solved by selecting the searching area based on the linear prediction of target motion. The experimental results have shown that the proposed scheme can make a mobile robot successfully follow a moving target in real time.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.767-771
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• 2003

In this study, stereo vision system is applied to a mobile manipulator for effective tasks. The robot can recognize a target and compute the position of the target using a stereo vision system. While a monocular vision system needs properties such as geometric shape of a target, a stereo vision system enables the robot to find the position of a target without additional information. Many algorithms have been studied and developed for an object recognition. However, most of these approaches have a disadvantage of the complexity of computations and they are inadequate for real-time visual servoing. However, color information is useful for simple recognition in real-time visual servoing. In this paper, we refer to about object recognition using colors, stereo matching method, recovery of 3D space and the visual servoing.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.5
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• pp.411-417
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• 2005

In this study, stereo vision system is applied to a mobile manipulator for effective tasks. The robot can recognize a target and compute the potion of the target using a stereo vision system. While a monocular vision system needs properties such as geometric shape of a target, a stereo vision system enables the robot to find the position of a target without additional information. Many algorithms have been studied and developed for an object recognition. However, most of these approaches have a disadvantage of the complexity of computations and they are inadequate for real-time visual servoing. Color information is useful for simple recognition in real-time visual servoing. This paper addresses object recognition using colors, stereo matching method to reduce its calculation time, recovery of 3D space and the visual servoing.

• Korean Journal of Cognitive Science
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• v.26 no.3
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• pp.357-375
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• 2015

In our daily life, the probability of target prevalence in visual search varies from very low to high. However, most laboratory studies of visual search used a fixed probability of target prevalence at 50%. The present study examined the properties of information processing during visual search where the probability of target prevalence was manipulated to vary from low (20%), medium (50%), to high (80%). The search items were made of simple shape stimuli, and search accuracy, signal detection measures, and reaction times (RTs) were analyzed for characterizing the effect of target prevalence on the information processing strategies for visual search. The analyses showed that the rates of misses increased whereas those of false alarms decreased in the search condition of low target prevalence, whereas the pattern was reversed in the high prevalence condition. Signal detection measures revealed that the target prevalence shifted response criterion (c) without affecting sensitivity (d'). In addition, RTs for correct rejection responses in the target-absent trials became delayed as the prevalence increased, whereas those for hits in the target-present trials were relatively constant regardless of the prevalence. The RT delay in the target-absent trials indicates that increased target prevalence made the 'quitting threshold' for search termination more conservative. These results support an account that the target prevalence effect in visual search arises from a shift of decision criteria and the subsequent changes in search information processing, while rejecting the account of a speed-accuracy tradeoff.

• Physical Therapy Korea
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• v.1 no.1
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• pp.92-97
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• 1994

It is well known that visual cues can improve the motor performance of Parkinsonian patients. Previous laboratory studies have examined the effects of visual cueing to the floor. This case study examined the effects of using a visual cue above eye level on the gait of a Parkinsonian man. It was found that cueing the patient to a target above eye level while waking not only improved the kinematic parameters of the gait cycle but also facilitated a more functional gait pattern with re-intergration of arm swing, rhythm, heel strike and a more erect posture. Visual targeting above eye level may serve as an important clinical tool for physiotherapists treating Parkinsonian patients.

• Journal of the Korea Society of Computer and Information
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• v.25 no.7
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• pp.57-64
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• 2020

In this paper, we propose an scalable re-detection for correlation filter in visual tracking. In real world, there are lots of target disappearances and reappearances during tracking, thus failure detection and re-detection methods are needed. One of the important point for re-detection is that a searching area must be large enough to find the missing target. For robust visual tracking, we adopt kernelized correlation filter as a baseline. Correlation filters have been extensively studied for visual object tracking in recent years. However conventional correlation filters detect the target in the same size area with the trained filter which is only 2 to 3 times larger than the target. When the target is disappeared for a long time, we need to search a wide area to re-detect the target. Proposed algorithm can search the target in a scalable area, hence the searching area is expanded by 2% in every frame from the target loss. Four datasets are used for experiments and both qualitative and quantitative results are shown in this paper. Our algorithm succeed the target re-detection in challenging datasets while conventional correlation filter fails.