[Zurück]


Zeitschriftenartikel:

A. Manzoor, H. Truong, A. Calatroni, D. Roggen, M. Bouroche, S. Clarke, V. Cahill, G. Tröster, S. Dustdar:
"Analyzing the impact of different action primitives in designing high-level human activity recognition systems";
Journal of Ambient Intelligence and Smart Environments, Volume 5 (2013), Number 5; S. 443 - 461.



Kurzfassung englisch:
Designing human activity recognition systems, an integral part of any ambient assisted living environment, is an active
area of research in the ubiquitous computing, wearable sensing, and computer vision communities. Yet most of the systems ignore
human body motion and arm motion action primitives to recognize high-level human activities and are limited to object usage
action primitives. Consequently, there is little understanding of the significance of these action primitives on the performance of
activity recognition systems. In this paper, we comparatively assess the role of the object usage action primitives, body motion
action primitives, and arms motion action primitives to recognize human activities of daily living. Our experiments show that the
body motion action primitives and arms motion action primitives are vital to recognize the human activities that do not involve
much interaction with the objects and the environment.

Schlagworte:
Human activity recognition, ambient assisted living, smart homes, sensing systems, machine learning


"Offizielle" elektronische Version der Publikation (entsprechend ihrem Digital Object Identifier - DOI)
http://dx.doi.org/10.3233/AIS-130223



Zugeordnete Projekte:
Projektleitung Schahram Dustdar:
SM4ALL


Erstellt aus der Publikationsdatenbank der Technischen Universitšt Wien.