Investigating Webcam-based Hand-tracking for Navigation in Micro-task Crowdsourcing

Bachelor thesis (2022)

Authors

S. El Hilali Electrical Engineering, Mathematics and Computer Science

Contributors

G.M. Allen Web Information Systems - EEMCS (mentor)
Ujwal Gadiraju Web Information Systems - EEMCS (graduation committee member)
Faculty
Electrical Engineering, Mathematics and Computer Science, Electrical Engineering, Mathematics and Computer Science
Copyright: © 2022 Safouane El Hilali
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Published Date

20-06-2022

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Abstract

The health of micro-task crowdsourcing workers, also called crowdworkers, is something that is overlooked in the micro-task crowdsourcing literature. Due to repetitive tasks, they can develop Repetitive Strain Injuries. To look into other ways of navigating Crowdsourcing Work Environments (CSWEs) outside the mouse and keyboard paradigm, we consider webcam-based hand-tracking in this paper. The main question we considered was which hand gestures were most suitable for navigating CSWEs. By having micro-task crowdworkers (n=14) test five methods of navigating CSWEs, we found that gestures which were considered easiest and most
useful were those that specified a single action in an interface catered to hand-tracking controls. Gestures which attempt to directly replace the mouse in a regular mouse-oriented interface were rated lower on usefulness and ease of use. We also found that most crowdworkers were unlikely to use hand gestures for progressing through related subtasks, since they were considered harder than using the keyboard and mouse.

Files

RP_final_paper_FINAL.pdf
(pdf | 0.181 Mb)
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