• Journal of Ocean Engineering and Technology
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• v.17 no.1
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• pp.1-7
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• 2003

Autonomous underwater vehicles (AUVs) are unmanned, underwater vessels that are used to investigate sea environments in the study of oceanography. Docking systems are required to increase the capability of the AUVs, to recharge the batteries, and to transmit data in real time for specific underwater works, such as repented jobs at sea bed. This paper presents a visual :em control system used to dock an AUV into an underwater station. A camera mounted at the now center of the AUV is used to guide the AUV into dock. To create the visual servo control system, this paper derives an optical flow model of a camera, where the projected motions of the image plane are described with the rotational and translational velocities of the AUV. This paper combines the optical flow equation of the camera with the AUVs equation of motion, and deriver a state equation for the visual servo AUV. Further, this paper proposes a discrete-time MIMO controller, minimizing a cost function. The control inputs of the AUV are automatically generated with the projected target position on the CCD plane of the camera and with the AUVs motion. To demonstrate the effectiveness of the modeling and the control law of the visual servo AUV simulations on docking the AUV to a target station are performed with the 6-dof nonlinear equations of REMUS AUV and a CCD camera.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.940-943
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• 1996

In teleoperating, as seeing the monitor screen obtained from a camera instituted in the working environment, human operator generally controls the slave arm. Because we can see only 2-D image in a monitor, human operator does not know the depth information and can not work with high accuracy. In this paper, we proposed a traded control method using an visual sensor for the purpose of solving this problem. We can control a teleoperation system with precision when we use the proposed algorithm. Not only a human operator command but also an autonomous visual sensor feedback command is given to a slave arm for the purpose of coincidence current image features and target image features. When the slave arm place in a distant place from the target position, human operator can know very well the difference between the desired image features and the current image features, but calculated visual sensor command have big errors. And when the slave arm is near the target position, the state of affairs is changed conversely. With this visual sensor feedback, human does not need coincide the detail difference between the desired image features and the current image features and proposed method can work with higher accuracy than other method without, sensor feedback. The effectiveness of the proposed control method is verified through series of experiments.

• Journal of Korea Multimedia Society
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• v.19 no.8
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• pp.1337-1344
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• 2016

As the visual effect frequently used in movies or animations, special effects are well suited for the creation of buildings or materials' destruction and collapse scenes. With the relevant programs developing technologically, the adoption of a real-time physically based-system makes it possible to realistically express dynamic simulations. In the large scale, the visual expression of such effects of destroying is satisfying enough, but most common programs of those effects fail to maximize visual effect generated with the cutting of small materials. Besides, to perform a heavy simulation process needs high-performance hardware and programs, where high costs would become a serious issue. For this reason, this paper suggests a solution optimized for the effect of small materials-cutting. The progress of each step shows technologies which trace movement with the state of the completion of the character's motions and then cut the material in real-time, finally led to the very realistic visual effect. Besides, using vector inner calculation to follow the motions of object and to realize cutting effect, this study provides an experiment that constructs visual effect for visualization from the basis of mathematical algorithm and it would be certainly as an educational material used for further researches.

• Journal of Korea Multimedia Society
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• v.20 no.12
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• pp.1865-1873
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• 2017

The feature-based visual SLAM requires 3D positions for the extracted feature points to perform 3D-2D motion estimation. LiDAR can provide reliable and accurate 3D position information with low computational burden, while stereo camera has the problem of the impossibility of stereo matching in simple texture image region, the inaccuracy in depth value due to error contained in intrinsic and extrinsic camera parameter, and the limited number of depth value restricted by permissible stereo disparity. However, the sparsity of LiDAR data may increase the inaccuracy of motion estimation and can even lead to the result of motion estimation failure. Therefore, in this paper, we propose three interpolation methods which can be applied to interpolate sparse LiDAR data. Simulation results obtained by applying these three methods to a visual odometry algorithm demonstrates that the selective bilinear interpolation shows better performance in the view point of computation speed and accuracy.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.133-137
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• 2005

In this paper, we investigate visual and quantitative analysis of different tastes in the liquids using multi-array chemical sensor (MACS) based on the ion-selective electrodes (ISEs), which is so called the electronic tongue (E-Tongue) system. We apply the Fuzzy C-means (FCM) algorithm combined with Principal Component Analysis (PCA), which can be used to reduce multi-dimensional data to two- or three-dimensional data, to classify visually data patterns detected by E-Tongue system. The proposed technique can be determined the cluster centers and membership grade of patterns through the unsupervised way. The membership grade of an unknown pattern, which does not shown previously, can be visually and analytically determined. Throughout the experimental trails, the E-tongue system combined with the proposed algorithms is demonstrated robust performance for visual and quantitative analysis for different tastes in the liquids.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.1
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• pp.392-412
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• 2018

Due to the semantic gap problem across different modalities, automatically retrieval from multimedia information still faces a main challenge. It is desirable to provide an effective joint model to bridge the gap and organize the relationships between them. In this work, we develop a deep image annotation and classification by fusing multi-modal semantic topics (DAC_mmst) model, which has the capacity for finding visual and non-visual topics by jointly modeling the image and loosely related text for deep image annotation while simultaneously learning and predicting the class label. More specifically, DAC_mmst depends on a non-parametric Bayesian model for estimating the best number of visual topics that can perfectly explain the image. To evaluate the effectiveness of our proposed algorithm, we collect a real-world dataset to conduct various experiments. The experimental results show our proposed DAC_mmst performs favorably in perplexity, image annotation and classification accuracy, comparing to several state-of-the-art methods.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.52-55
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• 1997

This paper discusses an automatic visual-servoing system, in which a laser and a CCD camera are used for imaging the pattern of joint groove. The algorithm used here is simple and robust to find out the gap width and gap center. As a consequence, the speed of algorithm is very fast and optimized. A feature of this system is that it processes only by summing the vertical line and horizontal line of screen without any image preprocessing in order to get the energy information of lines alternatively. It is practical and useful for the system requiring a fast process time of vision.

• Journal of the Korean Institute of Landscape Architecture
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• v.30 no.2
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• pp.1-11
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• 2002

The purpose of this study is to investigate landscape image and define elements of difference in visual preference of bridges on the Han River. To do this end, video was used as a media for the evaluation of the landscape image of 16 bridges on the Han River using a Semantic Differential scale. Data is collected by 50 students from Woosuk University, majoring landscape architecture. Final analysis utilized a total of 704 samples of data. Data is analyzed through descriptive statistics, and spatial image is analyzed by factor analysis algorithm Principle component analysis using Varimax method is applied far extraction and factor rotation. T-test is used to find the difference between the bridge type of preference with the data of factor score. Logistic regression is used to select the factors that influences the visual preference among the image factors. The results of this study can be summarized as follows; The image of whole bridges on the Han River is somewhat orderly, sequential and open. The degree of visual preference of unique bridge type is higher than normal but there are some differences in visual preference within the same type of structure. This suggests that the surrounding landscape is one of the important factor for visual preference. Factors covering the image of bridge are found to be 'aesthetic',　'structure','spatial factor', and 'shape'. Total variance is obtained as 60.4%. The aesthetic variables are the most important factor for visual preference and the structural factor presents no significant difference in visual preference between more preferred and less preferred bridges. Since the collapse of Songsu Bridge, we thought the structural factor is very important but the results of this study suggest that it is more important to consider the aesthetic and spatial factors of the bridge to increase the visual preference when planning and designing bridges. Simulations with more detailed data about surroundings should be utilized practical design.

• ETRI Journal
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• v.18 no.2
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• pp.61-74
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• 1996

We propose two new rate control schemes to improve MPEG-2 rate control in view of visual quality when scene changes happen. Two proposed schemes are characterized by real-time and non real-time improvement to reduce the impact of scene changes. We also propose a new target-bit prediction method using spatial activity of pictures and present a simple and efficient scene change detection scheme using signed difference of mean absolute difference (MAD). Computer simulation results show that the proposed real-time algorithm effectively alleviates visual quality degradation after scene changes. The proposed non real-time algorithm gives maximum 2 dB improvement in peak signal-to-noise ratio (PSNR) at a scene-changed picture, compared with MPEG-2 rate control scheme and it shows better quality than the real-time one.

• The Journal of Korea Robotics Society
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• v.3 no.3
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• pp.194-202
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• 2008

This paper describes a new method for indoor environment mapping and localization with stereo camera. For environmental modeling, we directly use the depth and color information in image pixels as visual features. Furthermore, only the depth and color information at horizontal centerline in image is used, where optical axis passes through. The usefulness of this method is that we can easily build a measure between modeling and sensing data only on the horizontal centerline. That is because vertical working volume between model and sensing data can be changed according to robot motion. Therefore, we can build a map about indoor environment as compact and efficient representation. Also, based on such nodes and sensing data, we suggest a method for estimating mobile robot positioning with random sampling stochastic algorithm. With basic real experiments, we show that the proposed method can be an effective visual navigation algorithm.