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Communication Dans Un Congrès Année : 2017

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

Résumé

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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Dates et versions

hal-01654868 , version 1 (04-12-2017)

Identifiants

Citer

Keiko Katsuragawa, Ankit Kamal, Edward Lank. Effect of Motion-Gesture Recognizer Error Pattern on User Workload and Behavior. IUI 2017 - 22nd annual meeting of the Intelligent User Interfaces community, Mar 2017, Limassol, Cyprus. pp.439-449, ⟨10.1145/3025171.3025234⟩. ⟨hal-01654868⟩
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