Foundations of computational photography and videography

在过去的十年中，计算摄影已经成为一个研究领域，有望彻底改变我们捕捉照片和视频以及与照片和视频互动的方式。随着数码相机变得无处不在并转变为成熟的计算设备，现在可以在图像采集之前、期间和之后插入重要的计算。这导致了对相机成像链的彻底反思--从在入射光到达传感器之前转换入射光的光学器件，到操作相机的控制算法，再到之后处理照片和视频的算法。 虽然该领域现在已经获得了很大的发展势头，但长期的进展需要解决仍然没有得到很好理解的基本成像和分析问题。在这个建议中，我集中在这些问题中的三个：（1）分析光传输，即，光如何流过被成像的场景;（2）实现多焦点摄影，即。设计一个可以同时拍摄许多不同焦点照片的相机;以及（3）推断出现在视频或个人照片集中的人、物体和环境的时变3D形状。 虽然我们的工作将以计算摄影应用为指导，但这些问题本身代表了我和我的团队一直在探索的计算机视觉和计算机图形核心研究的自然延续。

Over the last decade, computational photography has emerged as a research field that promises to revolutionize the way we capture and interact with photos and videos. With digital cameras becoming ubiquitous and turning into full-fledged computing devices, it is now possible to interject significant computation before, during and after image acquisition. This has led to a fairly radical re-thinking of the camera's imaging chain---from the optics that transform incident light before it reaches the sensor, to the control algorithms operating the camera, to the algorithms that process its photos and videos afterward. Although the field has now gained a lot of momentum, long-term progress requires tackling fundamental imaging and analysis problems that are still not well understood. In this proposal I focus on three of these problems: (1) analyzing light transport, ie., how light flows through the scene being imaged; (2) achieving multi-focal photography, ie. designing a camera that can take many differently-focused photos at once; and (3) inferring the time-varying 3D shape of people, objects and environments appearing in a video or personal photo collection. While our work will be guided by computational photography applications, the problems themselves represent a natural continuation of core research in computer vision and computer graphics that I have been exploring with my group.