DocumentCode
248962
Title
Enabling visual analysis in wireless sensor networks
Author
Baroffio, Luca ; Canclini, Antonio ; Cesana A.Redondi, M. ; Tagliasacchi, M. ; Dan, G. ; Eriksson, E. ; Fodor, V. ; Ascenso, Joao ; Monteiro, Pedro
Author_Institution
DEIB, Politec. di Milano Milano, Milan, Italy
fYear
2014
fDate
27-30 Oct. 2014
Firstpage
3408
Lastpage
3410
Abstract
This demo showcases some of the results obtained by the GreenEyes project, whose main objective is to enable visual analysis on resource-constrained multimedia sensor networks. The demo features a multi-hop visual sensor network operated by BeagleBones Linux computers with IEEE 802.15.4 communication capabilities, and capable of recognizing and tracking objects according to two different visual paradigms. In the traditional compress-then-analyze (CTA) paradigm, JPEG compressed images are transmitted through the network from a camera node to a central controller, where the analysis takes place. In the alternative analyze-then-compress (ATC) paradigm, the camera node extracts and compresses local binary visual features from the acquired images (either locally or in a distributed fashion) and transmits them to the central controller, where they are used to perform object recognition/tracking. We show that, in a bandwidth constrained scenario, the latter paradigm allows to reach better results in terms of application frame rates, still ensuring excellent analysis performance.
Keywords
Linux; Zigbee; cameras; data compression; feature extraction; image coding; object recognition; object tracking; wireless sensor networks; ATC paradigm; BeagleBones Linux computers; CTA paradigm; GreenEyes project; IEEE 802.15.4 communication capabilities; JPEG compressed image transmission; analyze-then-compress paradigm; application frame rates; bandwidth constrained scenario; camera node; central controller; compress-then-analyze paradigm; distributed image acquition; local binary visual feature compression; local binary visual feature extraction; local image acquition; multihop visual sensor network; object recognition; object tracking; resource-constrained multimedia sensor networks; visual analysis; visual paradigms; wireless sensor networks; Cameras; Feature extraction; Image coding; Object recognition; Transform coding; Visualization; Wireless sensor networks; ARM; Binary Local Visual Features; Object Recognition; Object Tracking; Visual Sensor Networks;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Processing (ICIP), 2014 IEEE International Conference on
Conference_Location
Paris
Type
conf
DOI
10.1109/ICIP.2014.7025690
Filename
7025690
Link To Document