论文标题
自然场景的高分辨率多曝光立体图像和视频数据库
A High Resolution Multi-exposure Stereoscopic Image & Video Database of Natural Scenes
论文作者
论文摘要
近年来,诸如VR头戴式耳机,AR眼镜,多视图显示,自由点电视等沉浸式显示器已成为新的展示技术,与传统显示相比,提供了更好的视觉体验和观众的参与度。随着3D视频和展示技术的发展,高动态范围(HDR)摄像机和显示器的消费市场迅速增长。缺乏适当的实验数据是3D HDR视频技术领域的主要研究工作的重要障碍。此外,足够的现实世界多曝光实验数据集的不可用是用于HDR成像研究的主要瓶颈,从而限制了观众的体验质量(QOE)。在本文中,我们介绍了在印度理工学院马德拉斯校园内捕获的多元化立体曝光数据集,该数据集是多元化的动植物的所在地。该数据集使用ZED立体相机捕获,并提供户外位置的复杂场景,例如花园,路边景观,节日场地,建筑物和室内地区,例如学术和居住区。所提出的数据集可容纳宽深度范围,复杂的深度结构,使物体运动复杂化,照明变化,丰富的色彩动态,纹理差异,除了通过移动摄像机和背景运动引入的重大随机性。拟议的数据集可公开向研究界公开使用。此外,详细描述了捕获,对齐和校准多曝光立体视频和图像的过程。最后,我们讨论了有关HDR成像,深度估计,一致的音调映射和3D HDR编码的进度,挑战,潜在用例和未来研究机会。
Immersive displays such as VR headsets, AR glasses, Multiview displays, Free point televisions have emerged as a new class of display technologies in recent years, offering a better visual experience and viewer engagement as compared to conventional displays. With the evolution of 3D video and display technologies, the consumer market for High Dynamic Range (HDR) cameras and displays is quickly growing. The lack of appropriate experimental data is a critical hindrance for the development of primary research efforts in the field of 3D HDR video technology. Also, the unavailability of sufficient real world multi-exposure experimental dataset is a major bottleneck for HDR imaging research, thereby limiting the quality of experience (QoE) for the viewers. In this paper, we introduce a diversified stereoscopic multi-exposure dataset captured within the campus of Indian Institute of Technology Madras, which is home to a diverse flora and fauna. The dataset is captured using ZED stereoscopic camera and provides intricate scenes of outdoor locations such as gardens, roadside views, festival venues, buildings and indoor locations such as academic and residential areas. The proposed dataset accommodates wide depth range, complex depth structure, complicate object movement, illumination variations, rich color dynamics, texture discrepancy in addition to significant randomness introduced by moving camera and background motion. The proposed dataset is made publicly available to the research community. Furthermore, the procedure for capturing, aligning and calibrating multi-exposure stereo videos and images is described in detail. Finally, we have discussed the progress, challenges, potential use cases and future research opportunities with respect to HDR imaging, depth estimation, consistent tone mapping and 3D HDR coding.