Multi-View Human Activity Recognition in Distributed Camera Sensor Networks

Sensors

Ehsan Adeli Mosabbeb¹  Kaamran Raahemifar² 

[1] Computer Engineering Department, Iran University of Science and Technology, Narmak, Tehran 16846-13114, Iran; E-Mail:;Department of Electrical and Computer Engineering, Ryerson University, 350 Victoria Street, Toronto, ON M5B 2K3, Canada

关键词: human activity recognition;    camera sensor networks;    consensus;    convex optimization;    matrix completion;    nuclear norm;   

DOI  :  10.3390/s130708750

来源: mdpi

【 摘 要 】

With the increasing demand on the usage of smart and networked cameras in intelligent and ambient technology environments, development of algorithms for such resource-distributed networks are of great interest. Multi-view action recognition addresses many challenges dealing with view-invariance and occlusion, and due to the huge amount of processing and communicating data in real life applications, it is not easy to adapt these methods for use in smart camera networks. In this paper, we propose a distributed activity classification framework, in which we assume that several camera sensors are observing the scene. Each camera processes its own observations, and while communicating with other cameras, they come to an agreement about the activity class. Our method is based on recovering a low-rank matrix over consensus to perform a distributed matrix completion via convex optimization. Then, it is applied to the problem of human activity classification. We test our approach on IXMAS and MuHAVi datasets to show the performance and the feasibility of the method.

【 授权许可】

CC BY   
© 2013 by the authors; licensee MDPI, Basel, Switzerland.