Abstract
We present PTPG (Poisson triangular pattern generator), a method that generates and optimizes triangular patterns for tokens on tangible surfaces. PTPG uses spatial information of markers to form triangular patterns and processes a template-matching algorithm to identify patterns. We introduce Poisson disk sampling to search patterns in the feature vector space and set sampling constraints to obtain patterns that meet the requirements of size, shape, and pattern distance. The patterns optimized by a shape constraint address the marker-loss problem caused by a common design of capacitive tokens, and therefore improve the recognition rate. We manufacture ten sets of prototype tokens based on the patterns generated by Poisson sampling and test these tokens on different devices. Experimental results show that our method provides more unique patterns than other heuristic methods, and the patterns are applicable to different tangible surfaces with high recognition rates.