Multimodal person tracking and attention classification
Conference Paper, Proceedings of 1st ACM SIGCHI/SIGART Conference on Human-Robot Interaction (HRI '06), pp. 347 - 348, March, 2006
Abstract
The problems of human detection, tracking, and attention recognition can be solved more effectively by integrating multiple sensory modalities, such as vision and range data. We present a system that uses a laser range scanner and a single camera to detect and track people, and to classify their attention relative to a socially interactive robot.
BibTeX
@conference{Michalowski-2006-9423,author = {Marek Piotr Michalowski and Reid Simmons},
title = {Multimodal person tracking and attention classification},
booktitle = {Proceedings of 1st ACM SIGCHI/SIGART Conference on Human-Robot Interaction (HRI '06)},
year = {2006},
month = {March},
pages = {347 - 348},
publisher = {ACM},
keywords = {Human-robot interaction, social robotics},
}
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