Improved local shape feature stability through dense model tracking

Daniel R. Canelhas, Todor Stoyanov, Achim J. Lilienthal

Publikation: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitragBegutachtung

3 Zitate (Scopus)

Abstract

In this work we propose a method to effectively remove noise from depth images obtained with a commodity structured light sensor. The proposed approach fuses data into a consistent frame of reference over time, thus utilizing prior depth measurements and viewpoint information in the noise removal process. The effectiveness of the approach is compared to two state of the art, single-frame denoising methods in the context of feature descriptor matching and keypoint detection stability. To make more general statements about the effect of noise removal in these applications, we extend a method for evaluating local image gradient feature descriptors to the domain of 3D shape descriptors. We perform a comparative study of three classes of such descriptors: Normal Aligned Radial Features, Fast Point Feature Histograms and Depth Kernel Descriptors; and evaluate their performance on a real-world industrial application data set. We demonstrate that noise removal enabled by the dense map representation results in major improvements in matching across all classes of descriptors as well as having a substantial positive impact on keypoint detection reliability.

OriginalspracheEnglisch
TitelIROS 2013
UntertitelNew Horizon, Conference Digest - 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems
Seiten3203-3209
Seitenumfang7
DOIs
PublikationsstatusVeröffentlicht - 2013
Extern publiziertJa
Veranstaltung2013 26th IEEE/RSJ International Conference on Intelligent Robots and Systems: New Horizon, IROS 2013 - Tokyo, Japan
Dauer: 3 Nov. 20138 Nov. 2013

Publikationsreihe

NameIEEE International Conference on Intelligent Robots and Systems
ISSN (Print)2153-0858
ISSN (elektronisch)2153-0866

Konferenz

Konferenz2013 26th IEEE/RSJ International Conference on Intelligent Robots and Systems: New Horizon, IROS 2013
Land/GebietJapan
OrtTokyo
Zeitraum3/11/138/11/13

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