Towards an intelligent framework for pressure-based 3D curve drawing

• Main Authors: Lai, C.-Y., Zakaria, N.
• Format: Article
• Published: Springer Verlag 2014
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84906739152&doi=10.1007%2f978-3-319-11650-1_6&partnerID=40&md5=e852cc5ea078151eb1e92acc78204734; http://eprints.utp.edu.my/32078/

The act of controlling pressure through pencil and brush appears effortless, but to mimic this natural ability in the realm of electronic medium using tablet pen device is difficult. Previous pressure based interaction work have explored various signal processing techniques to improve the accuracy in pressure control, but a one-for-all signal processing solutions tend not to work for different curve types. We propose instead a framework which applies signal processing techniques tuned to individual curve type. A neural network classifier is used as a curve classifier. Based on the classification, a custom combination of signal processing techniques is then applied. Results obtained point to the feasibility and advantage of the approach. The results are generally applicable to the design of pressure based interaction technique and possibly unlock the potential of pressure based system for richer interactions. © 2014 Springer International Publishing.