Effect of Motion-Gesture Recognizer Error Pattern on User Workload and Behavior

Keiko Katsuragawa 1 Ankit Kamal 1 Edward Lank 1, 2
2 MJOLNIR - Computing tools to empower users
Inria Lille - Nord Europe, CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189
Abstract : Bi-level thresholding is a motion gesture recognition technique that mediates between false positives, and false negatives by using two threshold levels: a tighter threshold that limits false positives and recognition errors, and a looser threshold that prevents repeated errors (false negatives) by analyzing movements in sequence. In this paper, we examine the effects of bi-level thresholding on the workload and acceptance of end-users. Using a wizard-of-Oz recognizer, we hold recognition rates constant and adjust for fixed versus bi-level thresholding. Given identical recognition rates, we show that systems using bi-level thresholding result in significant lower workload scores on the NASA-TLX and accelerometer variance. Overall , these results argue for the viability of bi-level thresholding as an effective technique for balancing between false positives, recognition errors and false negatives.
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Communication dans un congrès
IUI 2017 - International Conference on Intelligent User Interfaces, Mar 2017, Limassol, Cyprus. 〈10.1145/3025171.3025234〉
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Soumis le : lundi 4 décembre 2017 - 14:39:55
Dernière modification le : mercredi 6 décembre 2017 - 01:20:18

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Keiko Katsuragawa, Ankit Kamal, Edward Lank. Effect of Motion-Gesture Recognizer Error Pattern on User Workload and Behavior. IUI 2017 - International Conference on Intelligent User Interfaces, Mar 2017, Limassol, Cyprus. 〈10.1145/3025171.3025234〉. 〈hal-01654868〉

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