Motion Prediction in Gesture-based Collaborative Design Environments

Abstract

A collaborative design environment (CDE) is a shared environment over some communication networks. It allows remote users to interact with each other to perform some design tasks. To support collaborative design, the human hand is a very natural and convenient tool as it is capable of accomplishing diverse tasks such as pointing, gripping, twisting and tearing. However, there is not much work that considers using the human hand as input in CDEs, in particular over the Internet. The main reasons for this are that the Internet suffers from high network latency, which affects the interaction, and the human hand has many degrees of freedom, which adds additional challenges to synchronizing the collaboration. In this paper, we propose a prediction method specifically designed for human hand motion to address the network latency. Through a thorough analysis of human finger motion, we have identified various finger motion constraints. By considering these motion constraints, we propose a constraint-based motion prediction method for hand motion. We present a number of experiments to demonstrate the performance of our prediction method and the dead reckoning algorithm based on the proposed predictor.