• The Journal of Korean Society for School & Community Health Education
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• v.9 no.2
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• pp.81-90
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• 2008

Objectives: Since 80% of the information we get from the environment comes in through our eyes (Anshel JR, 1999), uncorrected visual problems negatively affect children's educational process and perceptual development. The objectives of this study were: 1st, to document the prevalence of learning related vision problem in primary school children. 2nd, to compare responses of children with those of parents on visual symptoms. Lastly, to determine if there is an association between visual symptoms and academic performance. Methods: We administered visual-symptom quality of life questionnaire developed by Oklahoma College of Optometry in Vision Development to 1031 primary school children and their parent. Visual symptoms responded by children and their parents were compared using Independent Sample t-test and the relation between visual symptoms and academic performance were calculated using Pearson Correlation tests. Results and Conclusions: The number of children who need further professional evaluation, that is visual-symptom scores were ${\geq}20$, reported by children(25%) was greater than that reported by parents(16%). And visual-symptom scores reported by children were significantly higher than those reported by parents in every grade(p<0.01, p<0.001). Visual symptoms reported by both children and parents were found to be inversely correlated to academic performance in every academic area and most of their correlations were statistically significant(p<0.05). Therefore, children with more visual-symptom reported by both group had negative effects on children's academic performance.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.3
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• pp.236-242
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• 2010

A GNSS/INS integration system can not provide navigation solutions if there are no available satellites. To overcome this problem, a vision sensor is integrated with this system. Since generally a vision aided integration system uses only feature point to compute navigation solutions, it has a problem in observability. In this case, additional landmarks, which is priory known points, can improve the observability. In this paper, the observability is evaluated using TOM/SOM matrix and Eigenvalues. There are always the observability problems in the feature-point-only case, but the landmark-use case is fully observable after the $2^{nd}$ update time. Consequently the landmarks ensure full observability, so the system performance can be improved.

• Journal of Korea Multimedia Society
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• v.17 no.9
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• pp.1041-1051
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• 2014

In this paper, we propose a new image alignment technique based on CUDA SURF in order to solve the initial image alignment problem that frequently occurs in machine vision applications. Machine vision systems using multi-spectral images have recently become more common for solving various decision problems that cannot be performed by the human vision system. These machine vision systems mostly use markers for the initial image alignment. However, there are some applications where the markers cannot be used and the alignment techniques have to be changed whenever their markers are changed. In order to solve these problems, we propose a new image alignment method for multi-spectral machine vision applications based on SURF extracting image features without depending on markers. In this paper, we propose an image alignment method that obtains a sufficient number of feature points from multi-spectral images using SURF and removes outlier iteratively based on a least squares method. We further propose an effective preliminary scheme for removing mismatched feature point pairs that may affect the overall performance of the alignment. In addition, we reduce the execution time by implementing the proposed method using CUDA based on GPGPU in order to guarantee real-time operation. Simulation results show that the proposed method is able to align images effectively in applications where markers cannot be used.

• The Journal of Fisheries Business Administration
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• v.44 no.3
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• pp.85-101
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• 2013

The foundation of any association or organization should include a mission, a vision, and strategic goals. Vision and mission are frequently discussed in academic and practitioner literature and accepted as key items in strategic decisions. But in these days, the words"change and crisis"are what companies are familiar with. They bringing about uncertainty led the companies to search for new strategies in order to specify their directions. In case of making proper direction for some organization, the role of management philosophy is most important. And also identifying, clarifying and communicating the management philosophy is now a major part of the planning process. This study examines the characteristics of management philosophy items which including mission and vision in Korean fisheries business with contents analysis. in order to achieve these purpose, this research analysing the mission, vision and CEO's greeting with the social network analysis(SNA) which is the most dominant technique in contents analysis. The SNA is evaluated that most popular, rigorous and firm methodology for analyzing, examining and revising some concepts or objects in the context of semantics. The findings of social network analysis show that some critical problems are existed. First, most of the fisheries company did not fully announce the mission and vision irrespective of one's size or scale. Second, there is some coverage insufficiency of stakeholders in mission and vision. And cutting edge topics like environmental problem, corporate social responsibility, consumer sovereignty are not included in management philosophy.

• Journal of information and communication convergence engineering
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• v.11 no.3
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• pp.207-215
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• 2013

In this paper, we address the challenging computer vision problem of obtaining a reliable facial expression analysis from a naturally interacting person. We propose a system that combines a 3D generic face model, 3D head tracking, and 2D tracker to track facial landmarks and recognize expressions. First, we extract facial landmarks from a neutral frontal face, and then we deform a 3D generic face to fit the input face. Next, we use our real-time 3D head tracking module to track a person's head in 3D and predict facial landmark positions in 2D using the projection from the updated 3D face model. Finally, we use tracked 2D landmarks to update the 3D landmarks. This integrated tracking loop enables efficient tracking of the non-rigid parts of a face in the presence of large 3D head motion. We conducted experiments for facial expression recognition using both framebased and sequence-based approaches. Our method provides a 75.9% recognition rate in 8 subjects with 7 key expressions. Our approach provides a considerable step forward toward new applications including human-computer interactions, behavioral science, robotics, and game applications.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.6
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• pp.314-321
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• 2019

The Self-Adaptive Vision Correction Algorithm (SAVCA) developed in this study was suggested for improving usability by modifying four parameters (Modulation Transfer Function Rate, Astigmatic Rate, Astigmatic Factor and Compression Factor) except for Division Rate 1 and Division Rate 2 among six parameters in Vision Correction Algorithm (VCA). For verification, SAVCA was applied to two-dimensional mathematical benchmark functions (Six hump camel back / Easton and fenton) and 30-dimensional mathematical benchmark functions (Schwefel / Hyper sphere). It showed superior performance to other algorithms (Harmony Search, Water Cycle Algorithm, VCA, Genetic Algorithms with Floating-point representation, Shuffled Complex Evolution algorithm and Modified Shuffled Complex Evolution). Finally, SAVCA showed the best results in the engineering problem (speed reducer design). SAVCA, which has not been subjected to complicated parameter adjustment procedures, will be applicable in various fields.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.2
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• pp.121-129
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• 2015

This paper presents a multiple vehicle recognition algorithm based on radar and vision sensor fusion for lane change assistance. To determine whether the lane change is possible, it is necessary to recognize not only a primary vehicle which is located in-lane, but also other adjacent vehicles in the left and/or right lanes. With the given sensor configuration, two challenging problems are considered. One is that the guardrail detected by the front radar might be recognized as a left or right vehicle due to its genetic characteristics. This problem can be solved by a guardrail recognition algorithm based on motion and shape attributes. The other problem is that the recognition of rear vehicles in the left or right lanes might be wrong, especially on curved roads due to the low accuracy of the lateral position measured by rear radars, as well as due to a lack of knowledge of road curvature in the backward direction. In order to solve this problem, it is proposed that the road curvature measured by the front vision sensor is used to derive the road curvature toward the rear direction. Finally, the proposed algorithm for multiple vehicle recognition is validated via field test data on real roads.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.1
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• pp.75-85
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• 2013

To acquire depth information using stereo vision, it is required to find correspondence points between stereo image pair. Conventional stereo vision systems usually use two cameras to get disparity data. Therefore, conventional stereo matching methods cannot resolve the tradeoff problem between accuracy and precision with respect to the length of baseline. Besides, belief propagation method, which is being used recently, has a problem that matching performance is dependent on the fixed weight parameter ${\lambda}$. In this paper, we propose a modified belief propagation stereo matching technique based on multi-baseline stereo vision to solve the tradeoff problem. The proposed method calculates EMAD(extended mean of absolute differences) as local evidence. And proposed method decides weight parameter ${\lambda}$ adaptively to local texture information. The proposed method shows higher initial matching performance than conventional methods and reached optimum solution in less iteration. The matching performance is increased about 4.85 dB in PSNR.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.46-49
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• 2002

One problem of vision-based eye-gazed detection is that it gives low resolution. Base on the displacement of the eyes, we proposed method for vision-based eye-gaze detection. While looking at difference positions on the screen, the distance of the centers of the eyes change accordingly. This relationship is derived and used to map the displacement to the distance in the screen. The experiments are performed to measure the accuracy and resolution to verify the proposed method. The results shown the accuracy of the screen mapping function for the horizontal plane are 76.47% and the error of this function be 23.53%

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.462-465
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• 2002

This paper deals with the problem of synthesis of stable and optimal grasps with unknown objects by 3-finger hand. Previous robot grasp research has analyzed mainly with either unknown objects 2D by vision sensor or unknown objects, cylindrical or hexahedral objects, 3D. Extending the previous work, in this paper we propose an algorithm to analyze grasp of unknown objects 3D by vision sensor. This is archived by two steps. The first step is to make a 3D geometrical model of unknown objects by stereo matching which is a kind of 3D computer vision technique. The second step is to find the optimal grasping points. In this step, we choose the 3-finger hand because it has the characteristic of multi-finger hand and is easy to modeling. To find the optimal grasping points, genetic algorithm is used and objective function minimizing admissible farce of finger tip applied to the object is formulated. The algorithm is verified by computer simulation by which an optimal grasping points of known objects with different angles are checked.