Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Self-Organizing Maps
Spatial Cognition, An Interdisciplinary Approach to Representing and Processing Spatial Knowledge
Spatial Cognition, An Interdisciplinary Approach to Representing and Processing Spatial Knowledge
Using Adaptive Tracking to Classify and Monitor Activities in a Site
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Application of the Self-Organizing Map to Trajectory Classification
VS '00 Proceedings of the Third IEEE International Workshop on Visual Surveillance (VS'2000)
Virtual environment trajectory analysis: a basis for navigational assistance and scene adaptivity
Future Generation Computer Systems
Virtual environment trajectory analysis: a basis for navigational assistance and scene adaptivity
Future Generation Computer Systems
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This study proposes a modular system for clustering on-line motion trajectories obtained while users navigate within a virtual environment. It presents a neural network simulation that gives a set of five clusters which help to differentiate users on the basis of efficient and inefficient navigational strategies. The accuracy of classification carried out with a self-organizing map algorithm was tested and improved to above 85% by using learning vector quantization. The benefits of this approach and the possibility of extending the methodology to the study of navigation in Human Computer Interaction are discussed.