Learning to Classify Observed Motor Behavior
Abstract
We present a representational format for observed movements The representation has a temporal structure relating components of a single complex movement. We also present OXBOW, an unsupervised learning system, which constructs classes of these movements. Empirical results indicate that the system builds abstract movement concepts with appropriate component structure allowing it to predict the latter portions of a partially observed movement.
Cite
Text
Iba. "Learning to Classify Observed Motor Behavior." International Joint Conference on Artificial Intelligence, 1991.Markdown
[Iba. "Learning to Classify Observed Motor Behavior." International Joint Conference on Artificial Intelligence, 1991.](https://mlanthology.org/ijcai/1991/iba1991ijcai-learning/)BibTeX
@inproceedings{iba1991ijcai-learning,
title = {{Learning to Classify Observed Motor Behavior}},
author = {Iba, Wayne},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {1991},
pages = {732-738},
url = {https://mlanthology.org/ijcai/1991/iba1991ijcai-learning/}
}