http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
Yu-Hyeon Won(원유현),Jin-Sung Kim(김진성),Byuong-Chan Park(박병찬),Young-Mo Kim(김영모),Seok-Yoon Kim(김석윤) 한국컴퓨터정보학회 2019 韓國컴퓨터情報學會論文誌 Vol.24 No.1
In this paper, we propose a efficient feature point extraction method that can solve the problem of performance degradation by introducing a preprocessing process when extracting feature points by utilizing the characteristics of 360-degree realistic media. 360-degree realistic media is composed of images produced by two or more cameras and this image combining process is accomplished by extracting feature points at the edges of each image and combining them into one image if they cover the same area. In this production process, however, the stitching process where images are combined into one piece can lead to the distortion of non-seamlessness. Since the realistic media of 4K-class image has higher resolution than that of a general image, the feature point extraction and matching process takes much more time than general media cases.
Byeong-Chan Park(박병찬),Jin-Sung Kim(김진성),Yu-Hyeon Won(원유현),Young-Mo Kim(김영모),Seok-Yoon Kim(김석윤) 한국컴퓨터정보학회 2019 韓國컴퓨터情報學會論文誌 Vol.24 No.1
One of critical issues in dealing with 360-degree realistic contents is the performance degradation in searching and recognition process since they support up to 4K UHD quality and have all image angles including the front, back, left, right, top, and bottom parts of a screen. To solve this problem, in this paper, we propose an efficient search and comparison method for 360-degree realistic contents. The proposed method first corrects the distortion at the less distorted regions such as front, left and right parts of the image excluding severely distorted regions such as upper and lower parts, and then it extracts feature points at the corrected region and selects the representative images through sequence classification. When the query image is inputted, the search results are provided through feature points comparison. The experimental results of the proposed method shows that it can solve the problem of performance deterioration when 360-degree realistic contents are recognized comparing with traditional 2D contents.