Interactive Parts Model: An Application to Recognition of On-line Cursive Script

Part of Advances in Neural Information Processing Systems 13 (NIPS 2000)

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Predrag Neskovic, Philip Davis, Leon Cooper


In this work, we introduce an Interactive Parts (IP) model as an alternative to Hidden Markov Models (HMMs). We tested both models on a database of on-line cursive script. We show that im(cid:173) plementations of HMMs and the IP model, in which all letters are assumed to have the same average width, give comparable results. However , in contrast to HMMs, the IP model can handle duration modeling without an increase in computational complexity.