Augmenting Humans in the Loop: Towards an Augmented Reality Object Labeling Application for Crowdsourcing Communities

Julian Schuir (), René Brinkhege (), Eduard Anton (), Thuy Duong Oesterreich (), Pascal Meier () and Frank Teuteberg ()
Additional contact information
Julian Schuir: University of Osnabrück
René Brinkhege: University of Osnabrück
Eduard Anton: University of Osnabrück
Thuy Duong Oesterreich: University of Osnabrück
Pascal Meier: German Research Center for Artificial Intelligence
Frank Teuteberg: University of Osnabrück

A chapter in Innovation Through Information Systems, 2021, pp 198-215 from Springer

Abstract: Abstract Convolutional neural networks (CNNs) offer great potential for business applications because they enable real-time object recognition. However, their training requires structured data. Crowdsourcing constitutes a popular approach to obtain large databases of manually-labeled images. Yet, the process of labeling objects is a time-consuming and cost-intensive task. In this context, augmented reality provides promising solutions by allowing an end-to-end process of capturing objects, directly labeling them and immediately embedding the data in training processes. Consequently, this paper deals with the development of an object labeling application for crowdsourcing communities following the design science research paradigm. Based on seven issues and twelve corresponding meta-requirements, we developed an AR-based prototype and evaluated it in two evaluation cycles. The evaluation results reveal that the prototype facilitates the process of object detection, labeling and training of CNNs even for inexperienced participants. Thus, our prototype can help crowdsourcing communities to render labeling tasks more efficient.

Keywords: Crowdsourcing; Labeling; Object recognition; Augmented reality (search for similar items in EconPapers)
Date: 2021
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:lnichp:978-3-030-86797-3_14

Ordering information: This item can be ordered from
http://www.springer.com/9783030867973

DOI: 10.1007/978-3-030-86797-3_14

Access Statistics for this chapter

More chapters in Lecture Notes in Information Systems and Organization from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().