• Journal of the Korea Computer Graphics Society
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• v.22 no.4
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• pp.1-9
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• 2016

In this paper we present a projection mapping system onto human's moving hand by a projector as information delivery media and Kinect to recognize hand motion. Most traditional projection mapping techniques project a variety of images onto stationary objects, however, our system provides new user experience by projecting images onto the center of the moving palm. We explain development process of the system, and production of content as applications on our system. We propose hardware organization and development process of open software architecture based on object oriented programming approach. For stable image projection, we describe a device calibration method between the projector and Kinect in three dimensional space, and a denoising technique to minimize artifacts from Kinect coordinates vibration and unstable hand tremor.

• The Journal of the Korea Contents Association
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• v.14 no.7
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• pp.103-114
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• 2014

This study intends to make a proposal the direction classification to develop the independent study of e-book's visualization. For this, we research into the e-book of Disney animation which achieved recognition in the literary value and amusement First of all, We grasp the meaning of the concept of e-book's aerial-image and perceptual principle. Next, We found the subject that starts the movement, and then observed the factor of the presentation to be possible to experience the actual spatial experience by the motion-produced cues. Through analysis process, We can classify the appearance elements, media, camera, and the readers' motion-produced cues into 13 parts and define as the codes. As we analysis the frequency of use of the analysis object, We separated it into the 46 combination exercises. According to the combination with the independent exercise, We separated them into 4 groups. There are the actual spatial experience, narrative spatial experience, the experience of characters. The basis for these, we can analyze the characteristics of the motion-produced cues. This study has the meaning of the expansion of e-book into the film language system by separating the e-book's narrative visualization type.

• Journal of Advanced Marine Engineering and Technology
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• v.38 no.9
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• pp.1112-1118
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• 2014

In this paper, we propose a local descriptor and a similarity measure that is robust to radiometic variations. The proposed local descriptor is made up Haar wavelet filter and it can contain frequency informations about the feature point and its surrounding pixels in fixed region, and it is able to describe feature point clearly under ununiform illumination condition. And a proposed similarity measure is combined with conventional entropy-based similarity and another similarities that is generated by local descriptor. It can reflect similarities between image regions accurately under radiometic illumination variations. We validate with experimental results on some images and we confirm that the proposed algorithm is more superior than conventional algorithms.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.10a
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• pp.227-232
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• 2003

Non-intrusive methods based on active remote IR illumination for eye tracking is important for many applications of vision-based man-machine interaction. One problem that has plagued those methods is their sensitivity to lighting condition change. This tends to significantly limit their scope of application. In this paper, we present a new real-time eye detection and tracking methodology that works under variable and realistic lighting conditions. eased on combining the bright-pupil effect resulted from IR light and the conventional appearance-based object recognition technique, our method can robustly track eyes when the pupils are not very bright due to significant external illumination interferences. The appearance model is incorporated in both eyes detection and tracking via the use of support vector machine and the mean shift tracking. Additional improvement is achieved from modifying the image acquisition apparatus including the illuminator and the camera.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.4
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• pp.470-477
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• 2009

Modular reconfigurable robots with physical docking capability easily adapt to a new environment and many studies are necessary for the modular robots. In this paper, we propose a vision-based fuzzy autonomous docking controller for the modular docking robots. A modular docking robot platform which performs real-time image processing is designed and color-based object recognition method is implemented on the embedded system. The docking robot can navigate to a subgoal near a target robot while avoiding obstacles. Both a fuzzy obstacle avoidance controller and a fuzzy navigation controller for subgoal tracking are designed. We propose an autonomous docking controller using the fuzzy obstacle avoidance and navigation controllers, absolute distance information and direction informations of robots from PSD sensors and a compass sensor. We verify the proposed docking control method by docking experiments of the developed modular robots in the various environments with different distances and directions between robots.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.2
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• pp.43-50
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• 2018

The camera is a key element in image-based three-dimensional positioning, and camera calibration, which properly determines the internal characteristics of such a camera, is a necessary process that must be preceded in order to determine the three-dimensional coordinates of the object. In this study, a new methodology was proposed to determine interior orientation parameters of a camera semi-automatically without being influenced by size and shape of checkerboard for camera calibration. The proposed method consists of exterior orientation parameters estimation using quaternion, recognition of calibration target, and interior orientation parameter determination through bundle block adjustment. After determining the interior orientation parameters using the chessboard calibration target, the three-dimensional position of the small 3D model was determined. In addition, the horizontal and vertical position errors were about ${\pm}0.006m$ and ${\pm}0.007m$, respectively, through the accuracy evaluation using the checkpoints.

• Journal of KIISE:Computing Practices and Letters
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• v.12 no.1
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• pp.56-65
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• 2006

Recently the study on service robots has been proliferated in many fields, and there are active developments for indoor services such as supporting for elderly people. It is important for robot to recognize objects and situations appropriately for effective and accurate service. Conventional object recognition methods have been based on the pre-defined geometric models, but they have limitations in indoor environments with uncertain situation such as the target objects are occluded by other ones. In this paper we propose a Bayesian network model to reason the probability of target objects for effective detection. We model the relationships between objects by activities, which are applied to non-static environments more flexibly. Overall structure is constructed by combining common-cause structures which are the units making relationship between objects, and it makes design process more efficient. We test the performance of two Bayesian networks for verifying the proposed Bayesian network model through experiments, resulting in accuracy of $86.5\%$ and $89.6\%$ respectively.

• Journal of Digital Convergence
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• v.11 no.10
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• pp.359-366
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• 2013

Due to the development and market expansion of image analysis and recognition technology, video security such as CCTV cameras and digital storage devices, are required for real-time monitoring systems and intelligent video security systems. This includes the development of more advanced technologies. A rotatable PTZ camera, in a CCTV camera system, has a zoom function so you can acquire a precise picture. However it can cause blind spots, and can not monitor two or more moving objects at the same time. This study concerns, the intelligent tracking of multiple moving objects, CCTV systems, and methods of video surveillance. An intelligent video surveillance system is proposed. It can accurately shoot broad areas and track multiple objects at the same time, much more effectively than using one fixed camera for an entire area or two or more PTZ cameras.

• Journal of KIISE:Software and Applications
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• v.31 no.5
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• pp.563-569
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• 2004

A set of Zernike moments has been successfully used for object recognition or content-based image retrieval systems. Real time applications using Zernike moments, however, have been limited due to its complicated definition. Conventional methods to compute Zernike moments fast have focused mainly on the radial components of the moments. In this paper, utilizing symmetric/anti-symmetric properties of Zernike basis functions, we propose a fast and efficient method for Zernike moments. By reducing the number of operations to one quarter of the conventional methods in the proposed method, the computation time to generate Zernike basis functions was reduced to about 20% compared with conventional methods. In addition, the amount of memory required for efficient computation of the moments is also reduced to a quarter. We also showed that the algorithm can be extended to compute the similar classes of rotational moments, such as pseudo-Zernike moments, and ART descriptors in same manner.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.3
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• pp.249-256
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• 2016

Recently, a number of techniques to ensure the free walking for the visually impaired and transportation vulnerable have been studied. As a device for free walking, there are such as a smart cane and smart glasses to use the computer vision, ultrasonic sensor, acceleration sensor technology. In a typical technique, such as techniques for finds object and detect obstacles and walking area and recognizes the symbol information for notice environment information. In this paper, we studied recognization algorithm of the selected symbols that are required to visually impaired, with the deep learning algorithm. As a results, Use CNN(Convolutional Nueral Network) technique used in the field of deep-learning image processing, and analyzed by comparing through experimentation with various deep learning architectures.