Yasuhiro WADA, Mitsuo KAWATO
A Theory for Cursive Handwriting Based on the Minimization Principle
Abstract:We propose a trajectory planning and control theory which provides explanations at the computational algorithm, representation, and hardware levels for continuous movement such as connected cursive handwriting. The hardware is based on our previously proposed forward-inverse-relaxation neural network (Wada and Kawato, 1993). Computationally, the optimization principle is the minimum torque-change criterion. At the representation level, hard constraints satisfied by a trajectory are represented as sets of via-points extracted from handwritten characters. Accordingly, we propose a via-point estimation algorithm that estimates via-points by repeating the trajectory formation of a character and the via-point extraction from the character. It is shown experimentally that for movements with a single via-point target, the via-point estimation algorithm can assign a point near the via-point target. Good quantitative agreement is found between human experimental data and the trajectories generated by the theory.