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Model-based tracking at 300hz using raw time-of-flight observations

  • Jan Stuhmer
  • , Sebastian Nowozin
  • , Andrew Fitzgibbon
  • , Richard Szeliski
  • , Travis Perry
  • , Sunil Acharya
  • , Daniel Cremers
  • , Jamie Shotton
  • Technical University of Munich
  • Microsoft Research
  • Microsoft Corporation

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

15 Scopus citations

Abstract

Consumer depth cameras have dramatically improved our ability to track rigid, articulated, and deformable 3D objects in real-time. However, depth cameras have a limited temporal resolution (frame-rate) that restricts the accuracy and robustness of tracking, especially for fast or unpredictable motion. In this paper, we show how to perform model-based object tracking which allows to reconstruct the object's depth at an order of magnitude higher frame-rate through simple modifications to an off-the-shelf depth camera. We focus on phase-based time-of-flight (ToF) sensing, which reconstructs each low frame-rate depth image from a set of short exposure 'raw' infrared captures. These raw captures are taken in quick succession near the beginning of each depth frame, and differ in the modulation of their active illumination. We make two contributions. First, we detail how to perform model-based tracking against these raw captures. Second, we show that by reprogramming the camera to space the raw captures uniformly in time, we obtain a 10x higher frame-rate, and thereby improve the ability to track fast-moving objects.

Original languageEnglish
Title of host publication2015 International Conference on Computer Vision, ICCV 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3577-3585
Number of pages9
ISBN (Electronic)9781467383912
DOIs
StatePublished - 17 Feb 2015
Event15th IEEE International Conference on Computer Vision, ICCV 2015 - Santiago, Chile
Duration: 11 Dec 201518 Dec 2015

Publication series

NameProceedings of the IEEE International Conference on Computer Vision
Volume2015 International Conference on Computer Vision, ICCV 2015
ISSN (Print)1550-5499

Conference

Conference15th IEEE International Conference on Computer Vision, ICCV 2015
Country/TerritoryChile
CitySantiago
Period11/12/1518/12/15

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