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2017年4月26日学术报告:Full-Dimensional Imaging and Camera Intelligence


添加时间:2017-04-29 18:35:39



报告题目:Full-Dimensional Imaging and Camera Intelligence

时间:2017年4月26日(星期三),下午2点30分

报告人:Boxin Shi

地点:中心教学楼824

 

Abstract:
An ordinary camera captures the real 3D scene as a projected 2D image with three channels. During this projection process, some scene information gets lost such as depth and surface normal, and some information gets compressed such as resolution and dynamic range. This presentation answers the questions what information has been lost and how to get them back by introducing the full-dimensional imaging framework. The lost and compressed information is restored as additional channels of a generalized image, e.g., a high-quality depth map with as high resolution as the 2D image, with state of the art computer vision algorithms, computational photography techniques, and novel camera prototyping. The concept of camera intelligence is then introduced to inspire the future research that complements artificial intelligence with camera design for solving visual computing problems that can never be solved using a conventional camera.
 
Bio:
Boxin Shi obtained his Ph.D. degree from the University of Tokyo (supervised by Prof. Katsushi Ikeuchi) in 2013. He worked as a Postdoctoral Fellow at MIT Media Lab (with Prof. Ramesh Raskar) in 2014, at Singapore University of Technology and Design and NTU (with Prof. Alex Kot) respectively in 2015. He joined the Artificial Intelligence Research Center at the National Institute of Advanced Industrial Science and Technology (AIST) as a Researcher in 2016. He did internship at Microsoft Research Asia (with Prof. Yasuyuki Matsushita) and National University of Singapore (with Prof. Ping Tan). His research interests are computational photography and physics-based computer vision. He serves as an area chair for MVA 17, and program committee members for CVPR/ICCV, and reviewers for TPAMI/IJCV.

 

 

 



作者:姜玮