• Title/Summary/Keyword: Stitching images

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A study on lighting angle for improvement of 360 degree video quality in metaverse (메타버스에서 360° 영상 품질향상을 위한 조명기 투사각연구)

  • Kim, Joon Ho;An, Kyong Sok;Choi, Seong Jhin
    • 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.

A Study on the Characteristics and Design Development of Upcycled Denim Fashion (업사이클 데님 패션의 특성 및 디자인 개발 연구)

  • Lee, Yeonji;Um, Sohee
    • Journal of Fashion Business
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    • v.22 no.2
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    • pp.51-60
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    • 2018
  • This research focuses on the development of upcycled denim fashion designs, whichis a more specific category within general upcycled fashion design. Characteristics of upcycled fashion design, which has been identified previously by researchers, include the following traits: environmentality, uniqueness, aesthetic appeal, availability, convertibility, and deconstructivity. The expression principles include recycling, substitution, recombination, and reduction. The result of the analysis of the denim fashion design characteristics, which is based on the theoretical analysis, has found. The external expression pattern consists of the deconstruction and reconstitution of materials, the avant-garde style and convertibility, the ability to mix and match materials and techniques, the production of zero waste, and the use of layering. The expression techniques used included decomposition, depaysement, weaving, cut-off, collage, assemblage, overlapping, connecting, attaching, and stitching. The inner meanings were identified as economicality through recycling, convertibility through rearranging, and the rarity and value of hand-made products. The result of the research applying the identified characteristics are as follows. First, developing and creating designs using modified denim and sub-materials with various expression patterns and techniques could provide completely new images unlike existing denim products. Second, modifying the details while maintaining the basic format of denim clothing could provide unique and new possibilities for upcycled denim fashion design. Third, environment-friendly models with creative designs were developed by recycling used denim materials. This reduced waste and energy while maximizing the use of resources. This study expects contribute to upcycled fashion design research by recognizing the unique characteristics and value of denim material.

Impact of scanning strategy on the accuracy of complete-arch intraoral scans: a preliminary study on segmental scans and merge methods

  • Mai, Hai Yen;Mai, Hang-Nga;Lee, Cheong-Hee;Lee, Kyu-Bok;Kim, So-yeun;Lee, Jae-Mok;Lee, Keun-Woo;Lee, Du-Hyeong
    • The Journal of Advanced Prosthodontics
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    • v.14 no.2
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    • pp.88-95
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    • 2022
  • PURPOSE. This study investigated the accuracy of full-arch intraoral scans obtained by various scan strategies with the segmental scan and merge methods. MATERIALS AND METHODS. Seventy intraoral scans (seven scans per group) were performed using 10 scan strategies that differed in the segmental scan (1, 2, or 3 segments) and the scanning motion (straight, zigzag, or combined). The three-dimensional (3D) geometric accuracy of scan images was evaluated by comparison with a reference image in an image analysis software program, in terms of the arch shape discrepancies. Measurement parameters were the intermolar distance, interpremolar distance, anteroposterior distance, and global surface deviation. One-way analysis of variance and Tukey honestly significance difference post hoc tests were carried out to compare differences among the scan strategy groups (α = .05). RESULTS. The linear discrepancy values of intraoral scans were not different among scan strategies performed with the single scan and segmental scan methods. In general, differences in the scan motion did not show different accuracies, except for the intermolar distance measured under the scan conditions of a 3-segmental scan and zigzag motion. The global surface deviations were not different among all scan strategies. CONCLUSION. The segmental scan and merge methods using two scan parts appear to be reliable as an alternative to the single scan method for full-arch intraoral scans. When three segmental scans are involved, the accuracy of complete arch scan can be negatively affected.

A Feature Point Extraction and Identification Technique for Immersive Contents Using Deep Learning (딥 러닝을 이용한 실감형 콘텐츠 특징점 추출 및 식별 방법)

  • Park, Byeongchan;Jang, Seyoung;Yoo, Injae;Lee, Jaechung;Kim, Seok-Yoon;Kim, Youngmo
    • Journal of IKEEE
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    • v.24 no.2
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    • pp.529-535
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    • 2020
  • As the main technology of the 4th industrial revolution, immersive 360-degree video contents are drawing attention. The market size of immersive 360-degree video contents worldwide is projected to increase from $6.7 billion in 2018 to approximately $70 billion in 2020. However, most of the immersive 360-degree video contents are distributed through illegal distribution networks such as Webhard and Torrent, and the damage caused by illegal reproduction is increasing. Existing 2D video industry uses copyright filtering technology to prevent such illegal distribution. The technical difficulties dealing with immersive 360-degree videos arise in that they require ultra-high quality pictures and have the characteristics containing images captured by two or more cameras merged in one image, which results in the creation of distortion regions. There are also technical limitations such as an increase in the amount of feature point data due to the ultra-high definition and the processing speed requirement. These consideration makes it difficult to use the same 2D filtering technology for 360-degree videos. To solve this problem, this paper suggests a feature point extraction and identification technique that select object identification areas excluding regions with severe distortion, recognize objects using deep learning technology in the identification areas, extract feature points using the identified object information. Compared with the previously proposed method of extracting feature points using stitching area for immersive contents, the proposed technique shows excellent performance gain.