CGV: Small: Collaborative Research: AdaCID: Adaptive Coded Imaging and Displays

这是一个合作项目，利用了阿肖克·维拉加万、威廉·马什·赖斯大学(IIS-1116718)和麻省理工学院拉梅什·拉斯卡尔(IIS-1116452)的专业知识。成像和显示设备无处不在，并在各种应用中使用。这些设备的空间分辨率、深度范围、深度分辨率、时间分辨率、帧速率和带宽通常是先验固定的。当被成像或显示的内容的分辨率和其他属性不完全模仿那些先验假设的分辨率和其他属性时，这导致低效(在利用可用资源方面)和不期望的伪像(混叠、模糊和噪声)。由于成像和显示设备都迅速变得多功能，因此需要开发能够调整其分辨率和带宽特性以匹配内容的成像和显示体系结构(和算法)。本项目的目标是开发适应场景、运动、几何、观察者或照明条件的成像和显示设备。这种自适应设备带来了性能改进和迄今未曾探索过的新功能。该研究议程被组织成四个智能主题：(1)建立能够有效探索设计空间的自适应编码成像和显示(AdaCID)的理论框架(2)设计适应场景几何、运动和照明的自适应编码成像系统(3)实时适应内容、观众位置、和人类视觉系统增强视觉外观和允许直观的3D交互，以及(4)编码反馈投影仪-相机系统的演示，使其能够快速获取范围和材料特征。预计AdaCID将对横跨消费者成像和显示、机器视觉和自动化、科学/医学成像以及显示和监视的各种应用产生深远影响。由于AdaCID和更广泛的计算成像和显示领域越来越重要，它们将被整合到莱斯大学和麻省理工学院提供的各种课程中。教育材料的广泛传播将通过参与免费的、开放许可的Connexion计划和开放式课程以及公共领域的博物馆倡议(在麻省理工学院博物馆)实现。该项目还为两所院校的学生提供了合作研究的机会。项目网站(http://cameraculture.media.mit.edu/AdaCID/)提供更多信息。

This is a collaborative project leveraging expertise of Ashok Veeraraghavan, William Marsh Rice University (IIS-1116718) and Ramesh Raskar, Massachusetts Institute of Technology (IIS-1116452). Imaging and display devices are all around us and are used in a variety of applications. The spatial resolution, depth range, depth resolution, temporal resolution, frame-rate and bandwidth of these devices are usually fixed a priori. When the resolution and other properties of the content being imaged or displayed does not exactly mimic those that were assumed a priori, this leads to inefficiencies (in utilizing available resources) and undesirable artifacts (aliasing, blurring and noise). Since both imaging and display devices are fast becoming multi-purpose, there is a need to develop imaging and display architectures (and algorithms) that are capable of adapting their resolution and bandwidth characteristics to match those of the content.The goal of this project is to develop imaging and display devices that adapt to scene, motion, geometry, viewer, or illumination conditions. Such adaptive devices lead to performance improvements and novel capabilities hitherto unexplored. This research agenda is organized into four intellectual thrusts: (1) the establishment a theoretical framework for Adaptive Coded Imaging and Displays (AdaCID) that enables efficient exploration of the space of designs (2) the design of adaptive coded imaging systems that adapt to scene geometry, motion, and illumination (3) the design of adaptive and interactive coded 2D/3D displays that adapt in real-time to content, viewer position, and the human visual system enhancing visual appearance and allowing intuitive 3D interaction and (4) the demonstration of coded feedback projector-camera systems enabling rapid acquisition of range and material characteristics.It is expected that AdaCID will have far-reaching impact to diverse applications spanning consumer imaging and displays, machine vision and automation, scientific/medical imaging and displays and surveillance. Since AdaCID and the broader field of computational imaging and displays is increasingly important, they will be integrated into various courses offered at Rice University and MIT. Broad dissemination of the educational material will be achieved through participation in the free, open-licensed Connexions program and OpenCourseWare and in public-domain museum initiatives (at the MIT Museum). This project also offers collaborative research opportunities for students at the two institutions. Project Website (http://cameraculture.media.mit.edu/AdaCID/) provides additional information.