Open Access

The Catchment Feature Model: A Device for Multimodal Fusion and a Bridge between Signal and Sense

EURASIP Journal on Advances in Signal Processing20042004:769219

Received: 24 October 2002

Published: 18 September 2004


The catchment feature model addresses two questions in the field of multimodal interaction: how we bridge video and audio processing with the realities of human multimodal communication, and how information from the different modes may be fused. We argue from a detailed literature review that gestural research has clustered around manipulative and semaphoric use of the hands, motivate the catchment feature model psycholinguistic research, and present the model. In contrast to "whole gesture" recognition, the catchment feature model applies a feature decomposition approach that facilitates cross-modal fusion at the level of discourse planning and conceptualization. We present our experimental framework for catchment feature-based research, cite three concrete examples of catchment features, and propose new directions of multimodal research based on the model.

Keywords and phrases

multimodal interaction gesture interaction multimodal communications motion symmetries gesture space use

Authors’ Affiliations

Vision Interfaces and Systems Laboratory, Center for Human Computer Interaction, Virginia Polytechnic Institute and State University


© Quek 2004