Cited By
View all- Hossain HAl Haiz Khan MRoy N(2018)DeActiveProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/32142692:2(1-23)Online publication date: 5-Jul-2018
Robust real-time human activity recognition from tracked face displacements
Pages 87 - 98
Abstract
We are interested in the challenging scientific pursuit of how to characterize human activities in any formal meeting situation by tracking people’s positions with a computer vision system. We present a human activity recognition algorithm that works within the framework of CAMEO (the Camera Assisted Meeting Event Observer), a panoramic vision system designed to operate in real-time and in uncalibrated environments. Human activity is difficult to characterize within the constraints that the CAMEO must operate, including uncalibrated deployment and unmodeled occlusions. This paper describes these challenges and how we address them by identifying invariant features and robust activity models. We present experimental results of our recognizer correctly classifying person data.
References
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Rybski, P.E., de la Torre, F., Patil, R., Vallespi, C., Veloso, M.M., Browning, B.: Cameo: The camera assisted meeting event observer. In: International Conference on Robotics and Automation, New Orleans (2004).
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- Robust real-time human activity recognition from tracked face displacements
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- FCT: Foundation for Science and Technology
- Microsoft Research: Microsoft Research
- IMB-Hot�is: IMB-Hot�is
- C�mara Municipal da Covilh�: C�mara Municipal da Covilh�
- Parque de Ci�ncia e Tecnologia da Covilh�, S.A.: Parque de Ci�ncia e Tecnologia da Covilh�, S.A.
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Springer-Verlag
Berlin, Heidelberg
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Published: 05 December 2005
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View all- Hossain HAl Haiz Khan MRoy N(2018)DeActiveProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/32142692:2(1-23)Online publication date: 5-Jul-2018