@inproceedings{beba3c7fcee041fc97212bfbea7dbbf0,
title = "Robust 3D Reconstruction Through Noise Reduction of Ultra-Fast Images",
abstract = "3D reconstruction from multiple view images has been studied extensively in computer vision tasks. In order to increase the accuracy of the 3D reconstruction, it is important to secure the number of image frames and to find feature points and match accurate feature points by minimizing the influence of noise from each image. When we acquired images from high-speed camera, it is possible to analyze phenomena and object movements that are difficult to see with the naked eye. However, when using a high-speed camera, problems such as increased data amount, light amount, focus, and noise occur due to an increase in resolution and shutter speed. In this paper, we propose a preprocessing method for feature point tracking and matching for robust 3D reconstruction in high-speed images. The experimental results confirm the validity compared with 3D reconstruction output from the original image and preprocessed image.",
keywords = "3D reconstruction, High-speed image, Image procession",
author = "Song, {Nu lee} and Park, {Jin Ho} and Kim, {Gye Young}",
note = "Publisher Copyright: {\textcopyright} 2021, Springer Nature Singapore Pte Ltd.; 11th International Conference on Computer Science and its Applications, CSA 2019 and 14th KIPS International Conference on Ubiquitous Information Technologies and Applications, CUTE 2019 ; Conference date: 18-12-2019 Through 20-12-2019",
year = "2021",
doi = "10.1007/978-981-15-9343-7_71",
language = "English",
isbn = "9789811593420",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "509--514",
editor = "Park, {James J.} and Fong, {Simon James} and Yi Pan and Yunsick Sung",
booktitle = "Advances in Computer Science and Ubiquitous Computing - CSA-CUTE 2019",
address = "Germany",
}