A non-linear model of shape and motion for tracking finger spelt American sign language

摘要

This work presents a piecewise linear approximation to non-linear Point Distribution Models for modelling the human hand. The work utilises the natural segmentation of shape space, inherent to the technique, to apply temporal constraints, which can be used with CONDENSATION to support multiple hypotheses and discontinuous jumps within shape space. This paper presents a novel method by which the one-state transitions of the English Language are projected into shape space for tracking and model prediction using an HMM like approach. The paper demonstrates that this model of motion provides superior results to that of other tracking approaches.