Video-radio fusion approach for target tracking in smart spaces

Smart Spaces are an emerging technology which is gathering interest in several domains of application since they allow to supply services and to interact with users in a pervasive way. One of their basic tasks regards the localization of the users in order to provide services in a personalized and location- based way. However since the guarded area is usually complex (e.g. with occlusions) and extent several sensors must be used. In this work video data acquired by video-cameras and radio signals of the WLAN, by which user can access to services, are jointly employed to improve the association between video track and radio identifier, and, through a two step temporal filtering, it is possible to enhance the system reliability. Results are presented in a simulated environment showing the effectiveness of the proposed approach.

[1]  Takeo Kanade,et al.  Algorithms for cooperative multisensor surveillance , 2001, Proc. IEEE.

[2]  Roger Y. Tsai,et al.  A versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf TV cameras and lenses , 1987, IEEE J. Robotics Autom..

[3]  Gaetano Borriello,et al.  Location Systems for Ubiquitous Computing , 2001, Computer.

[4]  Patrick Pérez,et al.  Data fusion for visual tracking with particles , 2004, Proceedings of the IEEE.

[5]  C. Regazzoni,et al.  Extraction of Aligned Video and Radio Information for Identity and Location Estimation in Surveillance Systems , 2004 .

[6]  K.J.R. Liu,et al.  Signal processing techniques in network-aided positioning: a survey of state-of-the-art positioning designs , 2005, IEEE Signal Processing Magazine.

[7]  C. Micheloni,et al.  A network of co-operative cameras for visual surveillance , 2005 .

[8]  F. Lavagetto,et al.  A Flexible Architecture for Ambient Intelligence Systems Supporting Adaptive Multimodal Interaction with Users , 2004 .

[9]  Richard P. Martin,et al.  The limits of localization using RSS , 2004, SenSys '04.

[10]  Ying Wu,et al.  A co-inference approach to robust visual tracking , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

[11]  Luca Benini,et al.  An integrated multi-modal sensor network for video surveillance , 2005, VSSN '05.

[12]  Carlo S. Regazzoni,et al.  The asymmetric generalized Gaussian function: a new HOS-based model for generic noise pdfs , 1996, Proceedings of 8th Workshop on Statistical Signal and Array Processing.