{"id":70,"date":"2017-05-03T20:04:06","date_gmt":"2017-05-03T20:04:06","guid":{"rendered":"http:\/\/localhost:50002\/?page_id=70"},"modified":"2017-05-09T08:04:05","modified_gmt":"2017-05-09T08:04:05","slug":"light-in-flight","status":"publish","type":"page","link":"https:\/\/light.informatik.uni-bonn.de\/research\/light-in-flight\/","title":{"rendered":"Light in Flight"},"content":{"rendered":"Transient imaging, or light-in-flight imaging, refers to the capture and analysis of light transport at nanosecond and picosecond scales. We develop devices and methods to enable the capture and processing of such data at low cost and unprecedented speed, and to robustly reconstruct 3D scene information within and even beyond the line of sight.\r\n

Publications<\/h4>\r\n

Super-Resolution Time-Resolved Imaging Using Computational Sensor Fusion<\/a><\/h4>Clara Callenberg, Ashley Lyons, Dennis den Brok, Areeba Fatima, Alejandro Turpin, Vytautas Zickus, Laura M. Machesky, Jamie A. Whitelaw, Daniele Faccio, Matthias B. Hullin<\/b>
Scientific Reports (Nature Publishing Group) 11, 1689 (2021), https:\/\/doi.org\/10.1038\/s41598-021-81159-x, 2021. \"Super-Resolution<\/a>

<\/i><\/p><\/div>

Low-Cost SPAD Sensing for Non-Line-Of-Sight Tracking, Material Classification and Depth Imaging<\/a><\/h4>Clara Callenberg, Zheng Shi, Felix Heide, Matthias B. Hullin<\/b>
ACM Transactions on Graphics 40 (4), Article 61 (Proc. SIGGRAPH 2021), 2021. \"Low-Cost<\/a>

<\/i><\/p><\/div>

Non-Line-of-Sight Reconstruction using Efficient Transient Rendering<\/a><\/h4>Julian Iseringhausen, Matthias B. Hullin<\/b>
ACM Transactions on Graphics 39 (1), 2020. \"Non-Line-of-Sight<\/a>

In this paper, we present an efficient renderer for three-bounce indirect transient light transport, and use it to reconstruct objects around corners to unprecedented accuracy.<\/i><\/p><\/div>

Deep Non-Line-of-Sight Reconstruction<\/a><\/h4>Javier Grau Chopite, Matthias B. Hullin, Michael Wand, Julian Iseringhausen<\/b>
Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020. \"Deep<\/a>

The first deep-learning framework for reconstructing object shapes around a corner.<\/i><\/p><\/div>

Neural network identification of people hidden from view with a single-pixel, single-photon detector<\/a><\/h4>Piergiorgio Caramazza, Alessandro Boccolini, Daniel Buschek, Matthias Hullin, Catherine F. Higham, Robert Henderson, Roderick Murray-Smith, Daniele Faccio <\/b>
Scientific Reports (Nature Publishing Group), 8, 11945; doi: 10.1038\/s41598-018-30390-0, 2018.

Machine Learning Assisted Identification of People Hidden Behind a Corner<\/a><\/h4>Piergiorgio Caramazza, Alessandro Boccolini, Gabriella Musarra, Matthias Hullin, Roderick Murray-Smith, Daniele Faccio<\/b>
Computational Optical Sensing and Imaging, 2017.

We demonstrate the use of machine learning to classify temporal histograms of the light-echoes backscattered from bodies hidden from view around a corner, captured by a SPAD camera.<\/i><\/p><\/div>

Material Classification using Raw Time-of-Flight Measurements<\/a><\/h4>Shuochen Su, Felix Heide, Robin Swanson, Jonathan Klein, Clara Callenberg, Matthias B. Hullin, Wolfgang Heidrich<\/b>
Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016. \"Material<\/a>

We show that using multi-frequency time-of-flight measurements, five different white materials can be distinguished on a per-pixel basis.<\/i><\/p><\/div>

Doppler Time-of-Flight Imaging<\/a><\/h4>Felix Heide, Wolfgang Heidrich, Matthias B. Hullin, Gordon Wetzstein<\/b>
ACM Transactions on Graphics (Proc. SIGGRAPH), 34 (4), 2015. \"Doppler<\/a>

A new computational imaging system that captures metric radial velocity information per pixel -- think of a huge array of traffic speed guns that use light instead of radar.<\/i><\/p><\/div>

Diffuse Mirrors: 3D Reconstruction from Diffuse Indirect Illumination using Inexpensive Time-of-Flight Sensors<\/a><\/h4>Felix Heide, Lei Xiao, Wolfgang Heidrich and Matthias B. Hullin<\/b>
Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2014. \"Diffuse<\/a>

How to look around a corner using echoes of light, using low-end devices that can't even properly measure such data.<\/i><\/p><\/div>

Low-Budget Transient Imaging using Photonic Mixer Devices<\/a><\/h4>Felix Heide*, Matthias B. Hullin*, James Gregson, Wolfgang Heidrich (* joint first authors)<\/b>
ACM Transactions on Graphics (Proc. SIGGRAPH), 32 (4), 2013. \"Low-Budget<\/a>

A computational method for capturing videos of light in flight using consumer-grade imaging hardware.<\/i><\/p><\/div>","protected":false},"excerpt":{"rendered":"

Transient imaging, or light-in-flight imaging, refers to the capture and analysis of light transport at nanosecond and picosecond scales. We develop devices and methods to enable the capture and processing of such data at low cost and unprecedented speed, and to robustly reconstruct 3D scene information within and even beyond the line of sight. Publications<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":68,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":[],"acf":[],"_links":{"self":[{"href":"https:\/\/light.informatik.uni-bonn.de\/wp-json\/wp\/v2\/pages\/70"}],"collection":[{"href":"https:\/\/light.informatik.uni-bonn.de\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/light.informatik.uni-bonn.de\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/light.informatik.uni-bonn.de\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/light.informatik.uni-bonn.de\/wp-json\/wp\/v2\/comments?post=70"}],"version-history":[{"count":8,"href":"https:\/\/light.informatik.uni-bonn.de\/wp-json\/wp\/v2\/pages\/70\/revisions"}],"predecessor-version":[{"id":242,"href":"https:\/\/light.informatik.uni-bonn.de\/wp-json\/wp\/v2\/pages\/70\/revisions\/242"}],"up":[{"embeddable":true,"href":"https:\/\/light.informatik.uni-bonn.de\/wp-json\/wp\/v2\/pages\/68"}],"wp:attachment":[{"href":"https:\/\/light.informatik.uni-bonn.de\/wp-json\/wp\/v2\/media?parent=70"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}