Time-Lapse Image Generation using Image-Based Modeling by Crowdsourcing
Time-Lapse Image Generation using Image-Based Modeling by Crowdsourcing
复制标题
通过众包使用基于图像的建模生成延时图像
DOI：
10.1109/bigdata.2018.8622254
复制
发表时间：
2019
期刊：
影响因子：
--
通讯作者：
I.Kitahara
中科院分区：
文献类型：
--
作者：
H.Shishido;E.Kawasaki;Y.Ito;Y.Kawamura;T.Matsui;I.Kitahara
近年来，世界遗产吴哥城巴戎寺的柱子因苔藓滋生而出现老化问题。我们的目标是生成图像来支持对柱子上苔藓繁殖的观察。即使在无法进行图像处理的环境下，我们也可以通过组合图像和3D形状之间的对应点来实现精确的叠加处理。为了生成观察目标的延时图像，需要许多不同捕获定时的精确图像。我们将使用大量通过众包收集的图像来制作延时图像。在本研究中，我们使用两种众包模型，以“捕获目标区域的图像”和“捕获图像的分类”作为微任务。因此，使用众包的图像采集和延时图像的生成是循环的。通过重复此流程，延时图像将会更加准确。
In recent years, the pillars of the World Heritage Angkor Thom Bayon temple have become a problem of deterioration due to moss breeding. We aim to generate an image to support observation of moss breeding on a pillar. Even under environment that prevent image processing, we can achieve accurate overlay processing by combining corresponding points between images and 3D shapes. In order to generate the timelapse image of the observation target, many accurate images of different capturing timings are necessary. We are going to use a lot of images collected by crowdsourcing for time lapse images. In this research, we use two crowdsourcing models with the "capturing image of the target region" and the "classification of the captured images" as the micro task. Therefore, image acquisition using crowdsourcing and generation of time lapse image are looped. Time lapse image will be more accurate by repeating this flow.