• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.9
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• pp.3196-3210
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• 2014

This paper presents a novel video metrology approach based on robust tracking. From videos acquired by an uncalibrated stationary camera, the foreground likelihood map is obtained by using the Codebook background modeling algorithm, and the multiple moving objects are tracked by a combined tracking algorithm. Then, we compute vanishing line of the ground plane and the vertical vanishing point of the scene, and extract the head feature points and the feet feature points in each frame of video sequences. Finally, we apply a single view mensuration algorithm to each of the frames to obtain height measurements and fuse the multi-frame measurements using RANSAC algorithm. Compared with other popular methods, our proposed algorithm does not require calibrating the camera, and can track the multiple moving objects when occlusion occurs. Therefore, it reduces the complexity of calculation and improves the accuracy of measurement simultaneously. The experimental results demonstrate that our method is effective and robust to occlusion.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.6
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• pp.143-148
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• 2022

It is very important for metaverse, mobile robot, and user location services to analyze the images continuously taken using a mobile smartphone or robot's monocular camera to estimate the camera's location. So far, PnP-related techniques have been applied to calculate the position. In this paper, the camera's moving direction is obtained using the essential matrix in the epipolar geometry applied to successive images, and the camera's continuous moving position is calculated through geometrical equations. A new estimation method was proposed, and its accuracy was verified through simulation. This method is completely different from the existing method and has a feature that it can be applied even if there is only one or more matching feature points in two or more images.

• Journal of Korea Multimedia Society
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• v.11 no.12
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• pp.1676-1687
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• 2008

In this paper, we proposed a new multi-view human recognition method based on face and gait features detection algorithm. For getting the position of moving object, we used the different of two consecutive frames. And then, base on the extracted object, the first important characteristic, walking direction, will be determined by using the contour of head and shoulder region. If this individual appears in camera with frontal direction, we will use the face features for recognition. The face detection technique is based on the combination of skin color and Haar-like feature whereas eigen-images and PCA are used in the recognition stage. In the other case, if the walking direction is frontal view, gait features will be used. To evaluate the effect of this proposed and compare with another method, we also present some simulation results which are performed in indoor and outdoor environment. Experimental result shows that the proposed algorithm has better recognition efficiency than the conventional sing]e view recognition method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.12C
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• pp.1154-1166
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• 2009

In this paper, we propose algorithms for generating high quality virtual intermediate views on the baseline or out of baseline. In this proposed algorithm, depth information as well as 3D warping technique is used to generate the virtual views. The coordinate of real 3D image is calculated from the depth information and geometrical characteristics of camera and the calculated 3D coordinate is projected to the 2D plane at arbitrary camera position and results in 2D virtual view image. Through the experiments, we could show that the generated virtual view image on the baseline by the proposed algorithm has better PSNR at least by 0.5dB and we also could cover the occluded regions more efficiently for the generated virtual view image out of baseline by the proposed algorithm.

• Journal of Broadcast Engineering
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• v.8 no.4
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• pp.452-464
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• 2003

In this paper, a multi-view 3D video processor was designed and implemented with several FPGAs for real-time applications. The 3D video processor receives 2D images from cameras (up to 16 cameras) and converts then to 3D video format for space-multiplexed 3D display. It can cope with various arrangements of 3D camera systems (or pixel arrays) and resolutions of 3D display. Tn order to verify the functions of 3D video Processor. some evaluation-board were made with five FPGAs.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.288-289
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• 2022

In this paper, we propose a method of obtaining high density geometric information using multi-view structured light. Reconstruction error due to the difference in resolution between the projector and the camera occurs when reconstruction a 3D shape from a structured light system to a single projector. This shows that the error in the point cloud in 3D is also the same when reconstruction the shape of the object. So we propose a high density method using multiple projectors to solve such a reconstruction error.

• 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.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1590-1591
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• 2011

In this paper, the UV corona camera was developed using the solar blind and Multi Channel Plate(MCP) technology for the target localization of UV camera. UV camera developed a $6.4^{\circ}{\times}4.8^{\circ}$ of the field of view as a conventional camera to diagnose a wide range of slightly enlarged, and power equipment to measure the distance between the camera and the distance meter has been attached. The UV camera was developed and measured using a UV image, as applied voltage increased ultraviolet images of the phenomenon could be obtained. And we investigated properties of UV corona image on insulator in salt water environments. From the results, the breakdown voltage was decreased and UV images were taken at low voltages and the UV image is rapidly increased with increasing High voltage.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.25.6-25
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• 2001

A new monitoring system is proposed to give direct visual information of the remote site when working with a tele-operation system. In order to have a similar behavior of a human when he is inspecting an object, multiple cameras that have different view point are attached around the robot hand and are switched on and elf according to the operator´s motion such as joystick manipulation or operator´s head movement. The performance of the system is estimated by performing comparison experiments among single camera (SC) vision system, head mount display (HMD)system and proposed multiple camera (MC) vision system by applying a task to several examines. The reality, depth feeling and controllability are estimated for the examines ...

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1307-1312
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• 2023

In this paper, we propose a hybrid camera system that combines cameras with different focal lengths and LiDAR (Light Detection and Ranging) sensors to address the core components of autonomous driving perception technology, which include object recognition and distance measurement. We extract objects within the scene and generate precise location and distance information for these objects using the proposed hybrid camera system. Initially, we employ the YOLO7 algorithm, widely utilized in the field of autonomous driving due to its advantages of fast computation, high accuracy, and real-time processing, for object recognition within the scene. Subsequently, we use multi-focal cameras to create depth maps to generate object positions and distance information. To enhance distance accuracy, we integrate the 3D distance information obtained from LiDAR sensors with the generated depth maps. In this paper, we introduce not only an autonomous vehicle platform capable of more accurately perceiving its surroundings during operation based on the proposed hybrid camera system, but also provide precise 3D spatial location and distance information. We anticipate that this will improve the safety and efficiency of autonomous vehicles.