Paper Info
Title
Real Time Noise Reduction to Identify Motion Parameters in AR Maintenance Scenario.
Abstract
Augmented reality is a field which improves user experience of the real environment by providing some relevant additional data. Understanding what happens in the workspace of the AR system in a maintenance context and for checking compliance of workers actions according to the expected ones are major challenges in this field. Usually, proposed approaches in literature are user centred and consist to gestures classification techniques. We opt to object centred methods. Indeed, when models are well configured, they provide information about motion between parts implied in assembly tasks which could be compared to predefined motion constraints. However, in real conditions, extracted motion curves are very noisy, may be difficult to exploit and may induce some AR systems misinterpretations. In this paper, we propose a method to reduce noise in real time in these curves based on Support Vector Machines confidence scores. The goal is to appropriately weaken false values and correctly straighten rotation axis according to the confidence we could have on pose estimation. Preliminary results are promising but the method still needs some improvements.
Year
DOI
Venue
2016
10.1109/ISMAR-Adjunct.2016.24
ADJUNCT PROCEEDINGS OF THE 2016 IEEE INTERNATIONAL SYMPOSIUM ON MIXED AND AUGMENTED REALITY (ISMAR-ADJUNCT)
Keywords
Field
DocType
Industrial Augmented Reality,Noise Reduction,Real-Time,Motion Recognition,Compliance
Data mining,Computer vision,User experience design,Noise measurement,Computer science,Workspace,Support vector machine,Feature extraction,Pose,Augmented reality,Artificial intelligence,Maintenance engineering
Conference
Citations 
PageRank 
References 
0
0.34
0
Authors
3
Name
Order
Citations
PageRank
Alia Rukubayihunga100.68
Jean-yves Didier27013.14
Samir Otmane37927.96