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Towards high-level human activity recognition through computer vision and temporal logic

: Ijsselmuiden, J.; Stiefelhagen, R.

Volltext urn:nbn:de:0011-n-1415250 (275 KByte PDF)
MD5 Fingerprint: df2886f0e92286a2aaa50a496b055242
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Erstellt am: 16.5.2013

Dillmann, R.; Beyerer, J.; Aziz, Z.:
KI 2010: Advances in artificial intelligence. 33rd Annual German Conference on AI : Karlsruhe, Germany, September 21 -24, 2010, proceedings
Berlin: Springer, 2010 (Lecture Notes in Artificial Intelligence 6359)
ISBN: 978-3-642-16110-0
ISBN: 3-642-16110-3
ISSN: 0302-9743
German Conference on Artificial Intelligence (KI) <33, 2010, Karlsruhe>
Konferenzbeitrag, Elektronische Publikation
Fraunhofer IOSB ()
activity recognition; computer vision; 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 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.