• Journal of Institute of Control, Robotics and Systems
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• v.19 no.12
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• pp.1061-1066
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• 2013

In the steel industry, the detection of tiny defects including its 3D characteristics on steel surfaces is very important from the point of view of quality control. A multi-spectral photometric stereo method is an attractive scheme because the shape of the defect can be obtained based on the images which are acquired at the same time by using a multi-channel camera. Moreover, the calculation time required for this scheme can be greatly reduced for real-time application with the aid of a GPU (Graphic Processing Unit). Although a more reliable shape reconstruction of defects can be possible when the numbers of available images are increased, it is not an easy task to construct a camera system which has more than 3 channels in the visible light range. In this paper, a new 6-channel camera system, which can distinguish the vertical/horizontal linearly polarized lights of RGB light sources, was developed by adopting two 3-CCD cameras and two polarized lenses based on the fact that the polarized light is preserved on the steel surface. The photometric stereo scheme with 6 images was accelerated by using a GPU, and the performance of the proposed system was validated through experiments.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.818-819
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• 2014

Recently there are many works conducted on utilizing the DIBR (Depth-Image-Based Rendering) based intermediate images for the three-dimensional displays that do not require the use of stereoscopic glasses. However the prior works have used expensive depth cameras to obtain high-resolution depth images since DIBR-based intermediate image generation method requires the accuracy for depth information. In this study, we have developed the simulation to generate multi-view intermediate images based on the depth and color images using Microsoft Kinect. This simulation aims to support the acquisition of multi-view intermediate images utilizing the low-resolution depth and color image from Kinect, and provides the integrated service for the quality evaluation of the intermediate images. This paper describes the architecture and the system implementation of this simulation program.

• Journal of Information Processing Systems
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• v.15 no.4
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• pp.904-919
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• 2019

Many security systems rely solely on solutions based on Artificial Intelligence, which are weak in nature. These security solutions can be easily manipulated by malicious users who can gain unlawful access. Some security systems suggest using fingerprint-based solutions, but they can be easily deceived by copying fingerprints with clay. Image-based security is undoubtedly easy to manipulate, but it is also a solution that does not require any special training on the part of the user. In this paper, we propose a multi-factor security framework that operates in a three-step process to authenticate the user. The motivation of the research lies in utilizing commonly available and inexpensive devices such as onsite CCTV cameras and smartphone camera and providing fully secure user authentication. We have used technologies such as Argon2 for hashing image features and physically unclonable identification for secure device-server communication. We also discuss the methodological workflow of the proposed multi-factor authentication framework. In addition, we present the service scenario of the proposed model. Finally, we analyze qualitatively the proposed model and compare it with state-of-the-art methods to evaluate the usability of the model in real-world applications.

• Journal of KIISE
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• v.43 no.5
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• pp.606-612
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• 2016

The multi-view video service based on the DASH(Dynamic Adaptive Streaming over HTTP) switches the viewpoint or object which is selected by the user among the multiple video streams captured by multiple cameras. However, the problem is that the conventional DASH-based multi-view video service takes a long time to switch the viewpoint. The reason is that the conventional scheme switches to the new video stream after consuming all buffered segments of the previous video stream. In this paper, we propose a video streaming scheme for minimizing the viewpoint switching delay in the DASH-based multi-view video service. In order to minimize the viewpoint switching delay, the proposed scheme configures the video streams by controlling the GoP (Group of Pictures) size and controls the client buffer based on bandwidth estimation and playback buffer occupancy. Through the experimental results, we prove that the proposed scheme reduces the viewpoint switching delay.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.7
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• pp.495-502
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• 2013

Motion estimation (ME) that limits the performance of image quality and encoding speed has been developed to reduce temporal redundancy in video sequences and plays an important role in digital video compression. But it is computational demanding part of the encoder. Multi-view video is obtained by capturing one three-dimensional scene with many cameras at different positions. ME for Multi-view video requires high computational complexity. To reduce computational complexity and maintain the image quality, a fast motion estimation method is proposed in this paper. The proposed method uses a hierarchical search strategy. This strategy method consists of modified diamond search patten, multi gird diamond search pattern, and raster search pattern. These search patterns place search points symmetrically and evenly that can cover the overall search area not to fall into the local minimum or exploits the characteristics of the distribution of motion vectors to place the search points. Experiment results show that the speedup improvement of the proposed method over TZ search method (JMVC) can be up to 1.2 ~3 times faster while maintaining similar video quality and bit rates.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.2
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• pp.261-271
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• 2009

Due to the recent rise of a need for 3 dimensional geospatial information on urban areas, general interest in aerial multi-view cameras has been on an increase. The conventional geospatial information system depends solely upon vertical images, while the multi-view camera is capable of taking both vertical and oblique images taken from multiple directions, thus making it easier for the user to interpret the object. Through our research we developed a prototype of a multi-view camera system that includes a camera system, GPS/INS, a flight management system, and a control system. We also studied and experimented with the camera viewing angles, the synchronization of image capture, the exposure delay, the data storage that must be considered for the development of the multi-view camera system.

• Journal of Korea Multimedia Society
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• v.17 no.3
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• pp.333-341
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• 2014

Multi-view video is obtained by capturing one three-dimensional scene with many cameras at different positions. Multi-view video coding requires high computational complexity. To reduce computational complexity and maintain the image quality, an effective early termination motion estimation method is proposed in this paper. The proposed method exploiting the characteristic of motion vector distribution uses a hierarchical search strategy. This strategy method consists of multi-grid square search pattern, modified diamond search pattern, small diamond search pattern and raster search pattern. Experiment results show that the speedup improvement of the proposed method over TZ search method and FS(Full Search) method JMVC (Joint Multiview Video Coding) can be up to 1.7~4.5 times and 90 times faster respectively while maintaining similar video quality and bit rates.

• Journal of Broadcast Engineering
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• v.25 no.5
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• pp.798-807
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• 2020

As technologies using digital camera have been developed, 3D images can be constructed from the pictures captured by using multiple cameras. The 3D image data is represented in a form of point cloud which consists of 3D coordinate of the data and the related attributes. Various techniques have been proposed to construct the point cloud data. Among them, Structure-from-Motion (SfM) and Multi-view Stereo (MVS) are examples of the image-based technologies in this field. Based on the conventional research, the point cloud data generated from SfM and MVS may be sparse because the depth information may be incorrect and some data have been removed. In this paper, we propose an efficient algorithm to enhance the point cloud so that the density of the generated point cloud increases. Simulation results show that the proposed algorithm outperforms the conventional algorithms objectively and subjectively.

• Journal of Korean Society for Geospatial Information Science
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• v.16 no.2
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• pp.67-76
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• 2008

Recently, one of the most outstanding technological characteristics of aerial survey is an application of Direct Georeferencing, which is based on the integration of main sensing sensors such as aerial camera or Lidar with positioning sensors GPS and IMU. In addition, a variety of digital aerial mapping cameras is developed and supplied with the verification of their technical superiority and applicability. In accordance with this requirement, the development of a multi-looking aerial photographing system is just making 3-D information acquisition and texture mapping possible for the dead areas arising from building side and high terrain variation where the use of traditional phptogrammetry is not valid. However, the development of a multi-looking camera integrating different sensors and multi-camera array causes some problems to conduct time synchronization among sensors and their geometric and radiometric calibration. The establishment of a test field for aerial sensor calibration is absolutely necessary to solve this problem. Therefore, this paper describes investigations for photogrammetric Test Field of foreign countries and suggest an establishment scheme for domestic test field.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.5
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• pp.667-674
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• 2023

In the event of a disaster occurring within a building, the prompt and efficient evacuation and rescue of occupants within the building becomes the foremost priority to minimize casualties. For the purpose of such rescue operations, it is essential to ascertain the distribution of individuals within the building. Nevertheless, there is a primary dependence on accounts provided by pertinent individuals like building proprietors or security staff, alongside fundamental data encompassing floor dimensions and maximum capacity. Consequently, accurate determination of the number of occupants within the building holds paramount significance in reducing uncertainties at the site and facilitating effective rescue activities during the golden hour. This research introduces a methodology employing computer vision algorithms to count the number of occupants within distinct building locations based on images captured by installed multiple CCTV cameras. The counting methodology consists of three stages: (1) establishing virtual Lines of Interest (LOI) for each camera to construct a multi-camera network environment, (2) detecting and tracking people within the monitoring area using deep learning, and (3) aggregating counts across the multi-camera network. The proposed methodology was validated through experiments conducted in a five-story building with the average accurary of 89.9% and the average MAE of 0.178 and RMSE of 0.339, and the advantages of using multiple cameras for occupant counting were explained. This paper showed the potential of the proposed methodology for more effective and timely disaster management through common surveillance systems by providing prompt occupancy information.