• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.8
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• pp.767-772
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• 2016

The purpose of this paper is to develop a gimbal system installed in the UFV(unmanned flight vehicles) for 360 degree VR video. In particular, even if the UFV rotated any direction the camera position is fiexd to minimize the shaking using the gyro sensor and the camera system is stable for taking $360^{\circ}$ panorama VR images.

• Journal of IKEEE
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• v.21 no.3
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• pp.268-271
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• 2017

In this paper, we propose the development of high resolution $360^{\circ}$ omnidirectional IP camera with 12 million pixels. The proposed 12-megapixel high-resolution $360^{\circ}$ omnidirectional IP camera consists of a lens unit with $360^{\circ}$ omnidirectional viewing angle and a 12-megapixel high-resolution IP camera unit. The lens section of $360^{\circ}$ omnidirectional viewing angle adopts the isochronous lens design method and the catadioptric facet production method to obtain the image without peripheral distortion which is inevitably generated in the fisheye lens. The 12 megapixel high-resolution IP camera unit consists of a CMOS sensor & ISP unit, a DSP unit, and an I / O unit, and converts the image input to the camera into a digital image to perform image distortion correction, image correction and image compression And then transmits it to the NVR (Network Video Recorder). In order to evaluate the performance of the proposed 12-megapixel high-resolution $360^{\circ}$ omnidirectional IP camera, 12.3 million pixel image efficiency, $360^{\circ}$ omnidirectional lens angle of view, and electromagnetic certification standard were measured.

• Journal of Broadcast Engineering
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• v.25 no.4
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• pp.518-527
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• 2020

360 VR technology is used not only in movies, but also in performing arts such as music, theater, dance, and so on due to the characteristics of immersion and presence. The technology allows the audience can be perceived a feel of participation in a story. This study is conducted an analysis of the techniques of 360 video shooting in order to find the answers of the following questionaries: how to make viewers enhance to a better understanding of a space, how to make the viewer feel comfortable ceding control of the experience, how to generate greater empathy with a 360 video. Thirty cases were analysed 360-degree videos of live performances performed on stage among 360-degree images of music performance content shared on Youtube from 2015 to 2020. The result shows that live performances are performed with the audience, so the stage shape and the layout of the audience seats are preferred to the characteristics of the performance. It was also shown that directing using a 360 VR camera was also greatly affected by the stage and audience placement. The stage is manly classified into three types, and the camera layout and characteristics mainly used are organized according to the number of 360 VR cameras, whether fixed or mobile cameras are used.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.517-518
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• 2022

본 논문에서는 360도 카메라기반 식물 전자 상거래서비스 어플을 제안한다. 식물을 이용한 재테크 일명 "식테크"라고 불리는 재테크가 증가하고 있는 추세이다. 현재 다른 중고거래 플랫폼에서는 본 거래가 제안되어 있어 거래가 어렵고 일종의 재테크의 개념이라 전문적으로 거래하기 힘들다는 문제점이 있다. 이를 해결하기 위해 본 프로젝트에서는 실시간 차트를 활용하여 식물 거래가를 알려주고, 360도 카메라와 VR을 활용하여 식물의 육성일기 공유하여 어플 사용자들의 커뮤니티 장소가 되고, 은퇴 후 귀농을 하는 사용자에게는 식물을 잘 기르는 법의 정보를 알 수 있는 다방면에서 활용이 가능하여 여러 문제를 효율적으로 해결할 것으로 기대된다.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.05a
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• pp.556-559
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• 2021

해당 연구는 Insta evo 360° 카메라로 촬영한 Equirectangular 형태의 영상을 활용하여 보행자에게 위험한 차량을 구분한 후 실시간적으로 차량 접근 알림을 주는 시스템에 관한 연구이다. 360° 영상 속 위험 차량 탐지와 추적을 위해 파노라마와 일반도로 이미지 데이터 세트로 전이학습 된 You Look Only Once v5 (YOLOv5), 객체 추적 알고리즘 Simple Online and Realtime Tracking with a Deep Association Metric (DeepSORT), 그리고 실험을 통해 개발한 비 위험 차량 필터링 알고리즘을 활용한다. Insta evo 360° 카메라를 머리 위에 얹어 촬영한 영상을 개발한 최종 시스템에 적용한 결과, 약 90% 정확도로 영상에서 비 위험 차량과 위험 차량을 구분할 수 있고, 위험 차량의 경우 차량의 방향을 시각적으로 알려줄 수 있다. 본 연구를 바탕으로 보행자 시야각 외부의 위험 차량에 대한 경고 알림을 주어 보행자 교통사고 발생 가능성을 줄이고, 전방위를 볼 수 있는 360° 카메라의 활용 분야가 보행 안전 시스템뿐만 아니라 더 다양해질 것으로 기대한다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2019.11a
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• pp.73-75
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• 2019

360°VR 영상은 카메라에서 촬영된 여러 영상들을 이어 붙이는 작업인 스티칭(Stitching)을 통하여 만들 수 있다. 스티칭은 영상들을 이어 붙이기 위해 각 영상의 특징점을 추출하는 특징점 추출, 특징점간 유사도를 비교하여 유사한 특징점끼리 매칭시키는 특징점 매칭, 특징점 매칭 과정에서 획득한 호모그래피 매트릭스를 이용한 이미지 와핑, 각 영상 간의 부자연스러운 경계선을 제거하는 블렌딩 과정을 거친다. 고품질의 360°VR 영상을 획득하기 위해서는 영상의 개수를 증가시킬 필요가 있고, 이로 인해 스티칭 과정에서 소요되는 시간이 증가한다. 본 논문에서는 카메라 센서 정보를 이용해 유사한 영상끼리 클러스터링하여, 한번에 스티칭이 진행되는 영상의 수를 감소시키고, 멀티 스레드를 이용하여 각 그룹의 스티칭을 병렬적으로 진행한 뒤, 최종적으로 스티칭하여 최종 360°VR 영상을 획득하는 과정을 제안한다.

• The Journal of the Convergence on Culture Technology
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• v.8 no.1
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• pp.499-505
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• 2022

Recently, the metaverse has been receiving a lot of attention. Metaverse means a virtual space, and various events can be held in this space. In particular, 360-degree video, a format optimized for the metaverse space, is attracting attention. A 360-degree video image is created by stitching images taken with multiple cameras or lenses in all 360-degree directions. When shooting a 360-degree video, a variety of shooting equipment, including a shooting staff to take a picture of a subject in front of the camera, is displayed on the video. Therefore, when shooting a 360-degree video, you have to hide everything except the subject around the camera. There are several problems with this shooting method. Among them, lighting is the biggest problem. This is because it is very difficult to install a fixture that focuses on the subject from behind the camera as in conventional image shooting. This study is an experimental study to find the optimal angle for 360-degree images by adjusting the angle of indoor lighting. We propose a method to record 360-degree video without installing additional lighting. Based on the results of this study, it is expected that experiments will be conducted through more various shooting angles in the future, and furthermore, it is expected that it will be helpful when using 360-degree images in the metaverse space.

• Journal of Broadcast Engineering
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• v.24 no.6
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• pp.1096-1112
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• 2019

The cameras generating 360 VR image are too expensive to be used publically. To overcome this problem, we propose a way to use smart phones instead of VR camera, where more than 100 pictures are taken by smart phone and are stitched into a 360 VR image. In this scenario, when moving objects are in some of the pictures, the stitched 360 VR image has various degradations, for example, ghost effect and mis-aligning. In this paper, we proposed an algorithm to modify the seam finding algorithms, where the saliency map in ROI is generated to check whether the pixel belongs to visually salient objects or not. Various simulation results show that the proposed algorithm is effective to increase the quality of the generated 360 VR image.

• Journal of Korea Society of Industrial Information Systems
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• v.22 no.3
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• pp.27-38
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• 2017

This Paper Presents a Method for Stitching a Large Number of Images Recorded by a Large Number of Individual Users Through a Cellular Phone Camera at a Venue. In Contrast to 360 Camera Solutions that Use Existing Fixed Rigs, these Conditions must Address New Challenges Such as Time Synchronization, Repeated Transformation Matrix Calculations, and Camera Sensor Mismatch Correction. In this Paper, we Solve this Problem by Updating the Transformation Matrix Using Time Synchronization Method Using Audio, Sensor Mismatch Removal by Color Transfer Method, and Global Operation Stabilization Algorithm. Experimental Results Show that the Proposed Algorithm Shows better Performance in Terms of Computation Speed and Subjective Image Quality than that of Screen Stitching.

• Journal of IKEEE
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• v.22 no.1
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• pp.68-73
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• 2018

In this paper, we propose an efficient algorithm for mapping a $360^{\circ}$ circular image to a planar image. The proposed algorithm consists of obtaining size of the planar image, calculating the distance between the camera and the planar image, calculating horizontal angle of camera and planar image, calculating vertical angle between camera and planar image, calculating the position of a pixel that matches pixels in a $360^{\circ}$ circular image to pixels in a planar image. Experiments were performed to evaluate the efficient algorithm for mapping the proposed $360^{\circ}$ circular image to the plane image. The reconstruction rate of the mapped plane image was confirmed 99% and the image quality of the mapped plane image was confirmed 72%. Since the results were higher than the standard values of commercial software, the effectiveness of the algorithm was confirmed.