DocumentCode :
727472
Title :
GreenEyes: Networked energy-aware visual analysis
Author :
Baroffio, L. ; Cesana, M. ; Redondi, A. ; Tagliasacchi, M. ; Ascenso, J. ; Monteiro, P. ; Eriksson, E. ; Dan, G. ; Fodor, V.
Author_Institution :
DEIB, Politec. di Milano, Milan, Italy
fYear :
2015
fDate :
June 29 2015-July 3 2015
Firstpage :
1
Lastpage :
4
Abstract :
The GreenEyes project aims at developing a comprehensive set of new methodologies, practical algorithms and protocols, to empower wireless sensor networks with vision capabilities. The key tenet of this research is that most visual analysis tasks can be carried out based on a succinct representation of the image, which entails both global and local features, while it disregards the underlying pixel-level representation. Specifically, GreenEyes will pursue the following goals: i) energy-constrained extraction of visual features; ii) rate-efficiency modelling and coding of visual feature; iii) networking streams of visual features. This will have a significant impact on several scenarios including, e.g., smart cities and environmental monitoring.
Keywords :
feature extraction; image coding; image representation; power aware computing; wireless sensor networks; GreenEyes project; energy-aware visual analysis; environmental monitoring; image representation; rate-efficiency modelling; smart city; visual feature coding; visual feature extraction; wireless sensor network; Algorithm design and analysis; Cameras; Encoding; Feature extraction; Image coding; Visualization; Wireless sensor networks; Local Visual Features; Visual Analysis; Visual Sensor Networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Multimedia & Expo Workshops (ICMEW), 2015 IEEE International Conference on
Conference_Location :
Turin
Type :
conf
DOI :
10.1109/ICMEW.2015.7169823
Filename :
7169823
Link To Document :
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