User Clustering Visualization and Its Impact on Motion-Based Interaction Design
Published in Lecture Notes in Computer Science book series (LNCS,volume 14011), 2023
Movement-based interaction design relies on sensor data analysis and higher-level feature extraction to represent human movement. However, challenges to effectively using movement data include building computational tools that allow exploring feature extraction technology as design material, and the need for visual representations that help designers better understand the contents of movement. This paper presents an approach for visualizing user clustering descriptors to enhance the practitioners’ ability to use human motion in interaction design. Read more
Recommended citation: Escamilla, A., Melenchón, J., Monzo, C., Moran, J.A. (2023). User Clustering Visualization and Its Impact on Motion-Based Interaction Design. In: Kurosu, M., Hashizume, A. (eds) Human-Computer Interaction. HCII 2023. Lecture Notes in Computer Science, vol 14011. Springer, Cham. https://doi.org/10.1007/978-3-031-35596-7_4 https://link.springer.com/chapter/10.1007/978-3-031-35596-7_4
