Imperial College London
Portrait Picture

ProfessorDenizGunduz

Faculty of Engineering, Department of Electrical and Electronic Engineering

Professor in Information Processing
 
 
 
//

Contact

 

+44 (0)20 7594 6218d.gunduz Website

 
 
//

Assistant

 

Ms Joan O'Brien +44 (0)20 7594 6316

 
//

Location

 

1016Electrical EngineeringSouth Kensington Campus

//

Summary

 

Publications

Citation

BibTex format

@article{Jankowski:2021:10.1109/JSAC.2020.3036955,
author = {Jankowski, M and Gunduz, D and Mikolajczyk, K},
doi = {10.1109/JSAC.2020.3036955},
journal = {IEEE Journal on Selected Areas in Communications},
pages = {89--100},
title = {Wireless image retrieval at the edge},
url = {http://dx.doi.org/10.1109/JSAC.2020.3036955},
volume = {39},
year = {2021}
}
Download

RIS format (EndNote, RefMan)

TY  - JOUR
AB  - We study the image retrieval problem at the wireless edge, where an edge device captures an image, which is then used to retrieve similar images from an edge server. These can be images of the same person or a vehicle taken from other cameras at different times and locations. Our goal is to maximize the accuracy of the retrieval task under power and bandwidth constraints over the wireless link. Due to the stringent delay constraint of the underlying application, sending the whole image at a sufficient quality is not possible. We propose two alternative schemes based on digital and analog communications, respectively. In the digital approach, we first propose a deep neural network (DNN) aided retrieval-oriented image compression scheme, whose output bit sequence is transmitted over the channel using conventional channel codes. In the analog joint source and channel coding (JSCC) approach, the feature vectors are directly mapped into channel symbols. We evaluate both schemes on image based re-identification (re-ID) tasks under different channel conditions, including both static and fading channels. We show that the JSCC scheme significantly increases the end-to-end accuracy, speeds up the encoding process, and provides graceful degradation with channel conditions. The proposed architecture is evaluated through extensive simulations on different datasets and channel conditions, as well as through ablation studies.
AU  - Jankowski,M
AU  - Gunduz,D
AU  - Mikolajczyk,K
DO  - 10.1109/JSAC.2020.3036955
EP  - 100
PY  - 2021///
SN  - 0733-8716
SP  - 89
TI  - Wireless image retrieval at the edge
T2  - IEEE Journal on Selected Areas in Communications
UR  - http://dx.doi.org/10.1109/JSAC.2020.3036955
UR  - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000599495400008&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR  - https://ieeexplore.ieee.org/document/9261169
UR  - http://hdl.handle.net/10044/1/86602
VL  - 39
ER  -
Download