• Journal of the Korea Computer Graphics Society
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• v.23 no.5
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• pp.9-17
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• 2017

Filming using multiple cameras is required for the production of the multi-screen content. It can fill the viewer's field of view (FOV) entirely to provide an increased sense of immersion. In such a filming scenario, it is very important to monitor how images captured by multiple cameras are displayed as a single content or how the content will be displayed in an actual theatre. Most recent studies on creating the content of special format have been focused on their own purposes, such as stereoscopic and panoramic images. There is no research on content creation optimized for theatres that use three screens that are spreading recently. In this paper, we propose a novel content production system with a rig that can control three cameras and monitoring software specialized for multi-screen content. The proposed rig can precisely control the angles between the cameras and capture wide angle of view with three cameras. It works with monitoring software via remote communication. The monitoring software automatically aligned the content in real time, and the alignment of the content is updated according to the angle of camera rig. Futher, the producion efficiency is greatly improved by making the alignment information available for post-production.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.3 s.309
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• pp.39-49
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• 2006

This paper proposes a hand-posture recognition method using reinforcement learning for the performance improvement of vision-based hand-posture recognition. The difficulties in vision-based hand-posture recognition lie in viewing direction dependency and self-occlusion problem due to the high degree-of-freedom of human hand. General approaches to deal with these problems include multiple camera approach and methods of limiting the relative angle between cameras and the user's hand. In the case of using multiple cameras, however, fusion techniques to induce the final decision should be considered. Limiting the angle of user's hand restricts the user's freedom. The proposed method combines angular features and appearance features to describe hand-postures by a two-layered data structure and reinforcement learning. The validity of the proposed method is evaluated by appling it to the hand-posture recognition system using three cameras.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.8
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• pp.309-314
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• 2014

To generate a complete 3D model from depth images of multiple RGB-D cameras, it is necessary to find 3D transformations between RGB-D cameras. This paper proposes a convenient view calibration technique using a spherical object. Conventional view calibration methods use either planar checkerboards or 3D objects with coded-pattern. In these conventional methods, detection and matching of pattern features and codes takes a significant time. In this paper, we propose a convenient view calibration method using both 3D depth and 2D texture images of a spherical object simultaneously. First, while moving the spherical object freely in the modeling space, depth and texture images of the object are acquired from all RGB-D camera simultaneously. Then, the external parameters of each RGB-D camera is calibrated so that the coordinates of the sphere center coincide in the world coordinate system.

• Korean Journal of Optics and Photonics
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• v.15 no.2
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• pp.183-189
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• 2004

As high quality digital cameras become readily available, digital cameras are being used not only for simple picture recording but also as information storing media in various fields. However, due to the fact that the spectral responses of the camera sensors are different from color matching functions of the CIE standard observer, the color can not be measured using these cameras. This study shows a method for converting camera image to sRGB image, in which color information is preserved. The transfer matrix between camera output signals and CIE stimulus values was determined using a multiple regression method with Macbeth ColorChecker as target colors. The CIE stimulus values for camera output signals can be mapped with a transfer matrix, and these values are converted to sRGB signals. As the result of testing a Kodak DC220 digital camera, the average color difference of Macbeth ColorChecker between true and displayed colors was 2.1 $\Delta$ $E_{ab}$ $^{*}$.$^{*}$.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.2
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• pp.234-239
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• 2021

Recently, as the installation of a large number of high-performance CCTVs for crime prevention and traffic control has increased rapidly, the problem of increasing system requirements for response to privacy infringement factors and analysis of high-definition image information transmitted from multiple cameras has been actively emerging. Accordingly, there is a need for a method for responding to privacy infringement and a method for efficiently processing surveillance images input from multiple cameras. In this paper, in order to reduce the processing cost of the input image and improve the processing speed, an integrated image is generated by grouping images input from a plurality of cameras. After analyzing the pre-generated integrated video, it detects a preset privacy event or an event that highlights interest. Depending on whether or not an event is detected, you will perform an editing operation corresponding to the event.

• Journal of Platform Technology
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• v.9 no.4
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• pp.60-70
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• 2021

This paper proposes a method capable of stably tracking the coordinates of a patterned laser image in a curved screen shooting system using two or more channels of multiple cameras. This method can track and acquire target points very effectively when applied to a multi-screen shooting method that can replace the HMD shooting method. Images of curved screens with severe deformation obtained from individual cameras are corrected through image normalization, image binarization, and noise removal. This corrected image is created and applied as an Euclidean space map that is easy to track the firing point based on the matching point. As a result of the experiment, the image coordinates of the pattern laser were stably extracted in the curved screen shooting system, and the error of the target point position of the real-world coordinate position and the broadband Euclidean map was minimized. The reliability of the proposed method was confirmed through the experiment.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1997.06a
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• pp.131-136
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• 1997

We present a method to estimate a dense and sharp depth map using multiple cameras for the application to flexible video production. A key issue for obtaining sharp depth map is how to overcome the harmful influence of occlusion. Thus, we first propose to selectively use the depth information from multiple cameras. With a simple sort and discard technique, we resolve the occlusion problem considerably at a slight sacrifice of noise tolerance. However, boundary overreach of more textured area to less textured area at object boundaries still remains to be solved. We observed that the amount of boundary overreach is less than half the size of the matching window and, unlike usual stereo matching, the boundary overreach with the proposed occlusion-overcoming method shows very abrupt transition. Based on these observations, we propose a hierarchical estimation scheme that attempts to reduce boundary overreach such that edges of the depth map coincide with object boundaries on the one hand, and to reduce noisy estimates due to insufficient size of matching window on the other hand. We show the hierarchical method can produce a sharp depth map for a variety of images.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.7
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• pp.634-640
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• 2015

This paper proposes a novel three-dimensional mapping algorithm in Omni-Directional Vision SLAM based on a fisheye image and laser scanner data. The performance of SLAM has been improved by various estimation methods, sensors with multiple functions, or sensor fusion. Conventional 3D SLAM approaches which mainly employed RGB-D cameras to obtain depth information are not suitable for mobile robot applications because RGB-D camera system with multiple cameras have a greater size and slow processing time for the calculation of the depth information for omni-directional images. In this paper, we used a fisheye camera installed facing downwards and a two-dimensional laser scanner separate from the camera at a constant distance. We calculated fusion points from the plane coordinates of obstacles obtained by the information of the two-dimensional laser scanner and the outline of obstacles obtained by the omni-directional image sensor that can acquire surround view at the same time. The effectiveness of the proposed method is confirmed through comparison between maps obtained using the proposed algorithm and real maps.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.6
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• pp.743-748
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• 2011

In this paper, we propose a collaborative tracking algorithm for intelligent video surveillance systems using the multiple network cameras. To do this, each camera detects a moving object and it's movement direction by motion templates. Once a moving object is detect, the Kalman filter is used to reduce noises, and a collaborative tracking camera is selected according to the movement direction and the camera state. In this procedure, Pan-Tilt-Zoom(PTZ) parameters are assigned to obtain clear images. Finally, some experiments show the validity of the proposed method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.357-358
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• 2021

Although many people watch the scene with multiple surveillance cameras, it is difficult to ensure that immediate action can be taken in the event of a crime. Therefore, there is a need for a "crime behavior detection system" that can analyze images in real time from multiple surveillance cameras installed in elevators, call immediate crime alerts, and track crime scenes and times effectively. In this paper, a study was conducted to detect violent scenes occurring in elevators using Scene Change Detection. For effective detection, an x2-color histogram combining color histogram and histogram was applied.