• Transactions of the Korean Society of Automotive Engineers
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• v.7 no.5
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• pp.162-171
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• 1999

The most important part in automated transport systems is steering control for lane keeping Most of systems developed so far have used the visual information for steering control. In this study, the steering control algorithm based on visual servoing has been developed and tested by applying it on Radio Controlled(R/C) model car equipped with one CCD camera. We also demonstrated the feasibility of using it as a pre-test car before the real car experiment in developing automated vehicles. In order to solve the problem of the limited spave and load of a model car, remote-brained approach has been taken. For steering control of a model car, the PD controller which uses the look ahead offset to generate control input has been implemented and the characteristics of the controller has been explained in view of kinematics. Some experimental results have been also illustrated so as to show the control performance and stability.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.53-53
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• 2002

According to glowing computing capacity, software in remote sensing has supported diverse processing interfaces from batch interface to high-end user interactive interface. In this paper, component based visual modeler is developed to process batch jobs for high-end users as well as novices. Visual modeler arranges several node groups which are categorized according to their purposes. These nodes carry out elemental unit processes and can be grouped to model. The model represents user specified job which is composed diverse nodes. User can organize models by connecting diverse nodes according to data flow model specification which rules node's connectivity and direction, etc. Furthermore, user defined models can be together to organize much more complex and large model.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.12
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• pp.547-552
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• 2014

As social multimedia sites are getting popular such as Flickr and Facebook, the amount of image information has been increasing very fast. So there have been many studies for accurate social image retrieval. Some of them were web image classification using semantic relations of image tags and BoVW(Bag of Visual Words). In this paper, we propose a method to detect salient region in images using GBVS(Graph Based Visual Saliency) model which can eliminate less important region like a background. First, We construct BoVW based on SIFT algorithm from the database of the preliminary retrieved images with semantically related tags. Second, detect salient region in test images using GBVS model. The result of image classification showed higher accuracy than the previous research. Therefore we expect that our method can classify a variety of images more accurately.

• Journal of Information Processing Systems
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• v.18 no.6
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• pp.813-821
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• 2022

Intelligent monitoring, life entertainment, medical rehabilitation, and other fields are only a few examples where visual image technology is becoming increasingly sophisticated and playing a significant role. Recognizing Wushu, or martial arts, movements through the use of visual image technology helps promote and develop Wushu. In order to segment and extract the signals of Wushu movements, this study analyzes the denoising of the original data using the wavelet transform and provides a sliding window data segmentation technique. Wushu movement The Wushu movement recognition model is built based on the hidden Markov model (HMM). The HMM model is trained and taught with the help of the Baum-Welch algorithm, which is then enhanced using the frequency weighted training approach and the mean training method. To identify the dynamic Wushu movement, the Viterbi algorithm is used to determine the probability of the optimal state sequence for each Wushu movement model. In light of the foregoing, an HMM-based martial arts movements recognition model is developed. The recognition accuracy of the HMM model increases to 99.60% when the number of samples is 4,000, which is greater than the accuracy of the SVM (by 0.94%), the CNN (by 1.12%), and the BP (by 1.14%). From what has been discussed, it appears that the suggested system for detecting martial arts acts is trustworthy and effective, and that it may contribute to the growth of martial arts.

• Journal of Gifted/Talented Education
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• v.20 no.1
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• pp.1-30
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• 2010

The purpose of this study was to develop the inspection model of cognitive ability to identify visual artistic giftedness of the elementary school children with considering the relation between visual artistic giftedness and cognitive ability based on literature and preceding research. The research method applied literature research and quantitative research. Through literature review on the relation between art education and cognitive thinking and visual artistic of giftedness, it was suggested to prescribe the validity of cognitive ability as an element for identification of visual artistic giftedness identification, and then prescribed the elements of cognitive ability, and developed the inspection model of cognitive ability by measuring specific variables. Based on the results of literature research through the quantitative research, verified significance of developed inspection instrument on cognitive ability, validity and reliability of the inspection model of cognitive ability according to visual artistic giftedness identification of the elementary school children. As a result of reviewing related literature and preceding research, it could be referred that visual thinking ability, spatial perception power and critical thinking ability coincided with a characteristic of an art field can show excellent ability in various art activities and be valid criteria of visual artistic giftedness as cognitive ability of the visual artistic gifted with potential possibilities. In conclusion, as the elements of cognitive ability for the visual artistic giftedness identification of the elementary school children, visual thinking ability, spatial perception power and critical thinking ability were verified to be valid in terms of logical and experimental. Therefore, the result of the research will be able to provide a new approach in education program development of visual artistic giftedness of the elementary school children and a various developmental possibility in identification of visual artistic giftedness.

• Korean Journal of Computational Design and Engineering
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• v.15 no.2
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• pp.136-143
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• 2010

Realistic Modeling is to maximize the reality of the environment in which perception is made by virtual environment or remote control using two or more senses of human. Especially, the field of haptic rendering, which provides reality through interaction of visual and tactual sense in realistic model, has brought attention. Haptic rendering calculates the force caused by model deformation during interaction with a virtual model and returns it to the user. Deformable model in the haptic rendering has more complexity than a rigid body because the deformation is calculated inside as well as the outside the model. For this model, Gibson suggested the 3D ChainMail algorithm using volumetric data. However, in case of the deformable model with non-homogeneous materials, there were some discordances between visual and tactual sense information when calculating the force-feedback in real time. Therefore, we propose an algorithm for the Volume Haptic Rendering of non-homogeneous deformable object that reflects the force-feedback consistently in real time, depending on visual information (the amount of deformation), without any post-processing.

• Journal of Korea Multimedia Society
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• v.25 no.10
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• pp.1386-1394
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• 2022

As consumption of high-quality fruits increases and sales and packaging units become smaller, the demand for automatic fruit grading systems is increasing. Compared to other crops, the quality of fruit is determined by visual characteristics such as shape, color, and scratches, rather than just physical size and weight. Accordingly, this study presents a CNN model that can effectively extract and classify the visual features of fruits and a perceptron that classifies fruits using physical features, and proposes a stacking ensemble model that can effectively combine the classification results of these two neural networks. The experiments with AI Hub public data show that the stacking ensemble model is effective for grading fruits. However, the ensemble model does not always improve the performance of classifying all the fruit grading. So, it is necessary to adapt the model according to the kind of fruit.

• Journal of Mechanical Science and Technology
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• v.14 no.7
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• pp.782-788
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• 2000

In this paper, we present a new approach to visual feedback control using image-based visual servoing with stereo vision. In order to control the position and orientation of a robot with respect to an object, a new technique is proposed using binocular stereo vision. The stereo vision enables us to calculate an exact image Jacobian not only around a desired location but also at other locations. The suggested technique can guide a robot manipulator to the desired location without providing a priori knowledge such as the relative distance to the desired location or the model of an object even when the initial positioning error is large. This paper describes a model of stereo vision and how to generate feedback commands. The performance of the proposed visual servoing system is illustrated by experimental results and compared with conventional control methods for an assembly robot.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.9A
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• pp.2313-2324
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• 1998

Although visual programming is used in many fields of computer science and engineering, some dis-advantages can be found when they work together in an integrated programming environment. To overcome these shortcomings, there have been researches in combining multiparadigm with visual programming. However they have failed because they tried to combine the paramdigms without any coceptural model and structured method. In this paper, we investigate a new multiparadigm visual programming environment (MVPE), in which dataflow paradigm, form-based paradign, direct manipulation paradigm, and object-oriented paradigm are integrated together in an object-oriented way, based on the conceptual model of "method = paradigm, " This MVPE would overcome the limits of visual programming, and may also lead to the new discipline of visual programming environment.vironment.

• Journal of Sensor Science and Technology
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• v.33 no.2
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• pp.78-85
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• 2024

We proposed a method for visual place recognition that represents images using objects as visual words. Visual words represent the various objects present in urban environments. To detect various objects within the images, we implemented and used a zero-shot detector based on a large-scale image language model. This zero-shot detector enables the detection of various objects in urban environments without additional training. In the process of creating histograms using the proposed method, frequency-based weighting was applied to consider the importance of each object. Through experiments with open datasets, the potential of the proposed method was demonstrated by comparing it with another method, even in situations involving environmental or viewpoint changes.