Real-Time 3D model tracking in color and depth on a single CPU core

Wadim Kehl, Federico Tombari, Slobodan Ilic, Nassir Navab

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

28 Scopus citations

Abstract

We present a novel method to track 3D models in color and depth data. To this end, we introduce approximations that accelerate the state-of-the-art in region-based tracking by an order of magnitude while retaining similar accuracy. Furthermore, we show how the method can be made more robust in the presence of depth data and consequently formulate a new joint contour and ICP tracking energy. We present better results than the state-of-the-art while being much faster then most other methods and achieving all of the above on a single CPU core.

Original languageEnglish
Title of host publicationProceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages465-473
Number of pages9
ISBN (Electronic)9781538604571
DOIs
StatePublished - 6 Nov 2017
Event30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017 - Honolulu, United States
Duration: 21 Jul 201726 Jul 2017

Publication series

NameProceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017
Volume2017-January

Conference

Conference30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017
Country/TerritoryUnited States
CityHonolulu
Period21/07/1726/07/17

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