Three-dimensional human-computer interaction has the potential to form the next generation of user interfaces and to replace the current 2D touch displays. To study and to develop such user interfaces, it is essential to be able to measure how a human behaves while interacting with them. In practice, this can be achieved by accurately measuring hand movements in 3D by using a camera-based system and computer vision. In this work, a framework for multi-camera finger movement measurements in 3D is proposed. This includes comprehensive evaluation of state-of-the-art object trackers to select the most appropriate one to track fast gestures such as pointing actions. Moreover, the needed trajectory post-processing and 3D trajectory reconstruction methods are proposed. The developed framework was successfully evaluated in the application where 3D touch screen usability is studied with 3D stimuli. The most sustainable performance was achieved by the Structuralist Cognitive model for visual Tracking tracker complemented with the LOESS smoothing.
CITATION STYLE
Lyubanenko, V., Kuronen, T., Eerola, T., Lensu, L., Kälviäinen, H., & Häkkinen, J. (2017). Multi-camera finger tracking and 3D trajectory reconstruction for HCI studies. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10617 LNCS, pp. 63–74). Springer Verlag. https://doi.org/10.1007/978-3-319-70353-4_6
Mendeley helps you to discover research relevant for your work.