“Do We Measure What We Perceive? Comparison of Perceptual and Computed Differences Between Hand Animations” by Justice, Adkins, Dong and Jörg

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Entry Number: 08

Title:

    Do We Measure What We Perceive? Comparison of Perceptual and Computed Differences Between Hand Animations

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Abstract:


    An increased interest in public motion capture data has allowed for the use of data-driven animation algorithms through neural networks. While motion capture data is increasingly accessible, data sets have become too large to sort through manually. Similarity metrics quantify how different two motions are and can be used to search databases much faster when compared to manual searches as well as to train neural networks. However, the most popular similarity metrics are not informed by human perception, resulting in the potential for data that is not perceptually similar being labeled as such by these metrics. We conducted an experiment with hand motions to identify how large the differences between human perception and common similarity metrics are. In this study, participants watched two animations of hand motions, one altered and the other unaltered, and scored their similarity on a 7-point Likert scale. In our comparisons, we found that none of the tested similarity metrics correlated with human judged scores of similarity.

References:


    Funda Durupinar. 2021. Perception of Human Motion Similarity Based on Laban Movement Analysis. In ACM Symposium on Applied Perception 2021 (Virtual Event, France) (SAP ’21). ACM, New York, NY, USA, Article 8, 7 pages. https://doi.org/10.1145/3474451.3476241Google ScholarDigital Library
    Sophie Jörg, Jessica Hodgins, and Carol O’Sullivan. 2010. The Perception of Finger Motions. In Proceedings of the 7th Symposium on Applied Perception in Graphics and Visualization (Los Angeles, California) (APGV ’10). ACM, New York, NY, USA, 129–133. https://doi.org/10.1145/1836248.1836273Google ScholarDigital Library
    Jan Sedmidubsky, Petr Elias, Petra Budikova, and Pavel Zezula. 2021. Content-Based Management of Human Motion Data: Survey and Challenges. IEEE Access 9(2021), 64241–64255. https://doi.org/10.1109/ACCESS.2021.3075766Google ScholarCross Ref
    Yingying Wang, Jean E Fox Tree, Marilyn Walker, and Michael Neff. 2016. Assessing the impact of hand motion on virtual character personality. ACM Transactions on Applied Perception (TAP) 13, 2 (2016), 1–23.Google ScholarDigital Library


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