【15-39期VALSE Webinar活动】  报告嘉宾：曹汛（南京大学）
报告时间：2015年12月30日（星期三）晚20:00（北京时间）
报告题目：High Resolution Spectral Video Capture and Computational Photography [Slides]
主持人：张兆翔（中科院自动化所）
报告摘要：Spectral capture technique collects information with more color channels than traditional trichromatic sensing. Therefore, it provides more detailed properties of the light source and the scene. Possible applications span across lots of fields such as remote sensing, materials science, bio-photonics, environmental monitoring, and so on. Spectral capture technique needs to record massive data in spatial, temporal and spectral domains, traditional spectral capture systems suffer from temporal and spatial scanning, thus is not suitable for video capture. Nowadays, with rapid development in sampling theory and electronic techniques, spectral video acquisition is becoming tractable. In this talk, we present recent progresses on the high resolution spectral video acquisition. Prism-Mask Imaging Spectrometer (PMIS) is proposed which accomplishes high quality video capture in three domains: spectral (1nm), spatial (one mega-pixels) and temporal (15 fps) resolution. Both the optical principle and the prototype setup of the PMIS are introduced. A bunch of computer vision applications (object tracking, skin detection, automatic white balance, etc) based on PMIS are demonstrated.
Besides the PMIS camera, in this talk, an emerging filed called Computational Photography is also introduced, which aims to overcome the limitations of the traditional camera by using computational techniques to produce a richer, more vivid, perhaps more perceptually meaningful representation of our visual world (quote from the CMU computational photography course introduction). With novel computational imaging techniques, we show amazing image/video galleries including gigapixel image/video, ultra-fast video capture (the speed of light), and light field modeling for digital movie industry.
参考文献：
[1] Ma C, Cao X*, Tong X, Dai Q, and Lin S. Acquisition of High Spatial and Spectral Resolution Video with a Hybrid Camera System. International Journal of Computer Vision (IJCV), Volume 110, Issue 2 (2014), Page 141-155
[2] Ma C, Cao X*, Wu R, and Dai Q. Content-adaptive high-resolution hyperspectral video acquisition with a hybrid camera system. Optics Letters, 39(4), 937-940, 2014
[3] Feng J, Fang X, Cao X*, et al. Advanced hyperspectral video imaging system using Amici prism. Optics express, 2014, 22(16): 19348-19356
[4] Yue, T., Suo, J., Wang, J., Cao, X., & Dai, Q. Blind Optical Aberration Correction by Exploring Geometric and Visual Priors. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1684-1692, 2015
报告人简介：Xun Cao received his Ph.D. degree from Tsinghua University, Beijing, China. He has been a visiting researcher at Philips Research, Aachen, Germany in 2008 and Microsoft Research Asia, in 2009 and 2010, and a visiting scholar at The University of Texas at Austin from 2010 to 2011. He joined the faculty at School of Electronic Science and Engineering, Nanjing University in 2012, and he is now an Associate Professor.
Dr. Cao’s research interests include Image Based Modeling and Rendering, 2D-to-3D Conversion and Computational Photography. His multi-view stereo modeling algorithm is Ranked No.1 accuracy according to the Middlebury vision evaluation. His 2D-to-3D conversion algorithm has been applied in the commercial software “Roxio Creator”, which has a major market share in North America. Dr. Cao also developed one of the first spectral video camera – PMIS (Prism-Mask Imaging Spectrometer), which can capture spectral information dynamically. Dr. Cao has published 27 papers on leading journals and conferences including IEEE T-PAMI, IJCV, CVPR, ICCV, etc, and he holds 30+ U.S. and China patents, he was awarded the First Prize of the National Technology Invention Award in 2012. |
