Towards High-Level Human Activity Recognition through Computer Vision and Temporal Logic
Most approaches to the visual perception of humans do not include high-level activity recognitition. This paper presents a system that fuses and interprets the outputs of several computer vision components as well as speech recognition to obtain a high-level understanding of the perceived scene. Our...
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Published in | KI 2010: Advances in Artificial Intelligence pp. 426 - 435 |
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Main Authors | , |
Format | Book Chapter |
Language | English |
Published |
Berlin, Heidelberg
Springer Berlin Heidelberg
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Series | Lecture Notes in Computer Science |
Subjects | |
Online Access | Get full text |
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Summary: | Most approaches to the visual perception of humans do not include high-level activity recognitition. This paper presents a system that fuses and interprets the outputs of several computer vision components as well as speech recognition to obtain a high-level understanding of the perceived scene. Our laboratory for investigating new ways of human-machine interaction and teamwork support, is equipped with an assemblage of cameras, some close-talking microphones, and a videowall as main interaction device. Here, we develop state of the art real-time computer vision systems to track and identify users, and estimate their visual focus of attention and gesture activity. We also monitor the users’ speech activity in real time. This paper explains our approach to high-level activity recognition based on these perceptual components and a temporal logic engine. |
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ISBN: | 9783642161100 3642161103 |
ISSN: | 0302-9743 1611-3349 |
DOI: | 10.1007/978-3-642-16111-7_49 |