• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.1
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• pp.53-59
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• 2008

Recently, vision-based hand gesture recognition techniques have been developed for assisting elderly and disabled people to control home appliances. Frequently occurred problems which lower the hand gesture recognition rate are due to the inter-person variation and intra-person variation. The recognition difficulty caused by inter-person variation can be handled by using user dependent model and model selection technique. And the recognition difficulty caused by intra-person variation can be handled by using fuzzy logic. In this paper, we propose multivariate fuzzy decision tree learning and classification method for a hand motion recognition system for multiple users. When a user starts to use the system, the most appropriate recognition model is selected and used for the user.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.4C
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• pp.494-504
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• 2004

The researches about gaze detection have been much developed with many applications. Most previous researches only rely on image processing algorithm, so they take much processing time and have many constraints. In our work, we implement it with a computer vision system setting a IR-LED based single camera. To detect the gaze position, we locate facial features, which is effectively performed with IR-LED based camera and SVM(Support Vector Machine). When a user gazes at a position of monitor, we can compute the 3D positions of those features based on 3D rotation and translation estimation and affine transform. Finally, the gaze position by the facial movements is computed from the normal vector of the plane determined by those computed 3D positions of features. In addition, we use a trained neural network to detect the gaze position by eye's movement. As experimental results, we can obtain the facial and eye gaze position on a monitor and the gaze position accuracy between the computed positions and the real ones is about 4.2 cm of RMS error.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.7
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• pp.90-103
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• 1999

In this paper, we present an overall algorithm for real-time camera parameter extraction which is one of key elements in implementing virtual studio. The prevailing mechanical methode for tracking cameras have several disadvantage such as the price, calibration with the camera and operability. To overcome these disadvantages we calculate camera parameters directly from the input image using computer-vision technique. When using zoom lenses, it requires real time calculation of lens distortion. But in Tsai algorithm, adopted for camera calibration, it can be calculated through nonlinear optimization in triple parameter space, which usually takes long computation time. We proposed a new method, separating lens distortion parameter from the other two parameters, so that it is reduced to nonlinear optimization in one parameter space, which can be computed fast enough for real time application.

• Journal of the Korea Society of Computer and Information
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• v.19 no.5
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• pp.99-107
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• 2014

In the past decade, Pine & Gilmore set out the vision for a new economic era, the experience economy, in which consumers are in search for extraordinary and memorable experiences. The purpose of this study is to investigate the relationships among walking tourist's experiences, walking tourist satisfaction and revisit intention as the social interest on walking tour has risen. A total of 250 respondents completed a survey. Using structural equation modeling (SEM) technique, the results reveal the effects of Esthetics(indulged in environments) and Escapism(diverging to a new self) that impact on walking tourist satisfaction and on revisit intention indirectly. Overall, finding of this study enhance the theoretical progress on the experiential concept in walking tour and offer important implication for walking tour marketers.

• The Journal of Korean Medical History
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• v.27 no.1
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• pp.61-76
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• 2014

The "ShikLyoChanYo", written in 1460 by JunSoonYi (全循義), master court doctor in JoSeon (朝鮮) Dynasty, is the very first specialty publication of Korean dietary treatment existing today. Both Chinese and Korean scholars have assumed that this book had been lost long time ago. In November 2003, however, a Korean philologist found a version of the book, Yangyang (襄陽, a district name in Korea), and this book has attracted a lot of interest of Korean traditional medical science and agricultural science since then. This paper is to dissert the document of food therapy from the book with profound document study and statistical analysis in the fields of traditional Chinese medicine and traditional Korean medicine on dietetics. It completes the study of the application of all the dietetic treatments according to symptoms of diseases and all the plants and medication applied to cure chronic conditions that are clinically examined for the purpose of food therapy. A general survey on sundry records related to this food therapy of the "ShikLyoChanYo" has been done to make this dissertation and it carried out a statistic analysis of all the dietetic mixing technique of all plants and medication. Among other symptoms of illnesses from the book, there are 7 frequently addressed ailments chosen from the aspect of food therapy - a stroke, a disease diagnosed by thirst, a serious cough, an ache resulting from numbness, a disease relating to stomach, blurry vision and weak hearing, and a drinking related disease. This part is to discuss these illnesses and how to cure them with food based on its characteristics and rules of application.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.3
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• pp.697-705
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• 2014

This paper presents a vision based object width measurement method and its application where the light sectioning method is employed. The target object for measurement is a tread, which is the most outside component of an automobile tire. The entire system applying the measurement method consists of two processes, i.e. a calibration process and a detection process. The calibration process is to identify the relationships between a camera plane and a laser plane, and to estimate a camera lens distortion parameters. As the process requires a test pattern, namely a jig, which is elaborately manufactured. In the detection process, first of all, the region that a laser light illuminates is extracted by applying an adaptive thresholding technique where the distribution of the pixel brightness is considered to decide the optimal threshold. Then, a thinning algorithm is applied to the region so that the ends and the shoulders of a tread are detected. Finally, the tread width and the shoulder width are computed using the homography and the distortion coefficients obtained by the calibration process.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.3
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• pp.310-315
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• 2004

Image taken in the night can be low-contrast images because of poor environment and image transmission. We propose an algorithm that improves the acquired low-contrast image. MPEG-2 separates chrominance and illuminance, and compresses respectively because human vision is more sensitive to luminance. We extracted illumination and used K-means algorithm to find a proper crossover point automatically. We used K-means algorithm in the viewpoint that the problem of crossover point selection can be considered as the two-category classification problem. We divided an image into two subimages using the crossover point, and applied the histogram equalization method respectively. We used the index of fuzziness to evaluate the degree of improvement. We compare the results of the proposed method with those of other methods.

• Journal of Biosystems Engineering
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• v.27 no.2
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• pp.133-142
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• 2002

This is a fundamental study to develop a sensor to detect weeds in paddy field using machine vision adopted spectralphotometric technique in order to use the sensor to spread herbicide selectively. A set of spectral reflectance data was collected from dry and wet soil and leaves of rice and 6 kinds of weed to select desirable wavelengths to classify soil, rice and weeds. Stepwise variable selection method of discriminant analysis was applied to the data set and wavelengths of 680 and 802 m were selected to distinguish plants (including rice and weeds) from dry and wet soil, respectively. And wavelengths of 580 and 680 nm were selected to classify rice and weeds by the same method. Validity of the wavelengths to distinguish the plants from soil was tested by cross-validation test with built discriminant function to prove that all of soil and plants were classified correctly without any failure. Validity of the wavelengths for classification of rice and weeds was tested by the same method and the test resulted that 98% of rice and 83% of weeds were classified correctly. Feasibility of CCD color camera to detect weeds in paddy field was tested with the spectral reflectance data by the same statistical method as above. Central wavelengths of RGB frame of color camera were tried as tile effective wavelengths to distingush plants from soil and weeds from plants. The trial resulted that 100% and 94% of plants in dry soil and wet soil, respectively, were classified correctly by the central wavelength or R frame only, and 95% of rice and 85% of weeds were classified correctly by the central wavelengths of RGB frames. As a result, it was concluded that CCD color camera has good potential to be used to detect weeds in paddy field.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.2 no.3
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• pp.53-60
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• 2009

The vision-based driver fatigue detection is one of the most prospective commercial applications of facial expression recognition technology. The facial feature tracking is the primary technique issue in it. Current facial tracking technology faces three challenges: (1) detection failure of some or all of features due to a variety of lighting conditions and head motions; (2) multiple and non-rigid object tracking; and (3) features occlusion when the head is in oblique angles. In this paper, we propose a new active approach. First, the active IR sensor is used to robustly detect pupils under variable lighting conditions. The detected pupils are then used to predict the head motion. Furthermore, face movement is assumed to be locally smooth so that a facial feature can be tracked with a Kalman filter. The simultaneous use of the pupil constraint and the Kalman filtering greatly increases the prediction accuracy for each feature position. Feature detection is accomplished in the Gabor space with respect to the vicinity of predicted location. Local graphs consisting of identified features are extracted and used to capture the spatial relationship among detected features. Finally, a graph-based reliability propagation is proposed to tackle the occlusion problem and verify the tracking results. The experimental results show validity of our active approach to real-life facial tracking under variable lighting conditions, head orientations, and facial expressions.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2004.05b
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• pp.603-607
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• 2004

The vision-based driver fatigue detection is one of the most prospective commercial applications of facial expression recognition technology. The facial feature tracking is the primary technique issue in it. Current facial tracking technology faces three challenges: (1) detection failure of some or all of features due to a variety of lighting conditions and head motions; (2) multiple and non-rigid object tracking and (3) features occlusion when the head is in oblique angles. In this paper, we propose a new active approach. First, the active IR sensor is used to robustly detect pupils under variable lighting conditions. The detected pupils are then used to predict the head motion. Furthermore, face movement is assumed to be locally smooth so that a facial feature can be tracked with a Kalman filter. The simultaneous use of the pupil constraint and the Kalman filtering greatly increases the prediction accuracy for each feature position. Feature detection is accomplished in the Gabor space with respect to the vicinity of predicted location. Local graphs consisting of identified features are extracted and used to capture the spatial relationship among detected features. Finally, a graph-based reliability propagation is proposed to tackle the occlusion problem and verify the tracking results. The experimental results show validity of our active approach to real-life facial tracking under variable lighting conditions, head orientations, and facial expressions.