| ||报告人： ||袁鑫 |
| ||美国贝尔实验室 |
|报告题目： ||Computational Photography: From Lensless Camera to Virtual Reality with A Stop at Hyperspectral Imaging |
|报告时间： ||2017年9月15日（周五）上午10:00 |
|报告地点： ||西区·溢智厅 |
|报告人简介 ||报告简介 ||本期论坛海报 ||本期论坛照片 ||本期论坛简讯 |
袁鑫博士现任美国贝尔实验室视频分析与编码首席研究员。袁鑫博士2009年在西安电子科技大学雷达信号处理重点实验室获得硕士学位后到香港理工大学攻读博士学位，2012年4月获取博士学位后到美国。在加入贝尔实验室之前，从2012年5月到2015年3月，袁鑫博士在美国杜克大学电子与计算机系从事博士后研究。主要研究方向为压缩感知，图像处理，机器学习，计算机视觉等。袁鑫博士迄今共发表了35篇国际期刊文章和30篇国际会议文章。袁鑫博士有2篇会议文章获得了Computational Optical Sensing and Imaging (COSI) 最佳论文奖，受邀参加中美工程院组织的2017年中美工程前沿论坛（CAFOE），担任10余个国际顶级期刊的审稿人，包括IEEE Transactions on Signal Processing, IEEE Transactions on Image Processing, IEEE Transactions on Aerospace and Electronic Systems, SIAM Journal on Imaging Science, Signal Processing, Digital Signal Processing, Optics Express 等。
Xin Yuan is currently a video analysis and coding lead researcher at Bell Labs, Murray Hill, NJ, USA. Prior to this, he had been a Post-Doctoral Associate with the Department of Electrical and Computer Engineering, Duke University from 2012 to 2015, where he was working on compressive sensing and machine learning. He develops compressive sensing techniques for high-dimensional imaging with applications to videos, hyperspectral, microscopy and x-ray imaging. Before joining Duke, Dr. Yuan obtained his B.Eng and M.Eng from Xidian University in 2007 and 2009, respectively, and his Ph.D. from the Hong Kong Polytechnic University in 2012. Two papers he coauthored won the best paper award in the Computational Optical Sensing and Imaging (COSI) conferences in 2013 and 2014, on video compressive sensing and on depth compressive sensing cameras, respectively.
Computational photography is an emerging field with continuing advances in both theory and applications. Computational photography has led to diverse imaging applications, including two-dimensional images, videos, hyperspectral images, depth, x-ray, millimeter wave, polarization, microscopy and Terahertz imaging. In this talk, we will start from the lensless camera, and based on the space-time-spectrum tradeoff, introduce the underlying principle of spatial/video/spectral computational imaging. The imaging architectures of various computational cameras will be described. As a pivot role in computational imaging, reconstruction will be introduced too. Aiming to bridge the gap in virtual reality, compressive high-speed 3D imaging systems will be discussed.