TY - GEN
T1 - Object recognition in extended image databases using a mobile client-server architecture
AU - Lehiani, Yassine
AU - Preda, Marius
AU - Maidi, Madjid
AU - Gabrielli, Adrian
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2016/2/17
Y1 - 2016/2/17
N2 - This paper presents a novel approach for object recognition in extended image databases using a mobile client-server architecture. The proposed approach relies upon feature detection and description to characterize textured objects within the image. The similarity search is performed on descriptor arrays by computing the distance between the query descriptor compared with reference descriptors extracted offline. The key contributions of the approach are the high accuracy, the time-effectiveness and the scalability of the method towards large image datasets. The developed method is first, integrated on a mobile platform and, then, deployed on a client-server architecture to deal with high volume image galleries. Experiments are performed to evaluate the performances of the system in real-life environment conditions and the obtained results demonstrate the relevance of the proposed approach.
AB - This paper presents a novel approach for object recognition in extended image databases using a mobile client-server architecture. The proposed approach relies upon feature detection and description to characterize textured objects within the image. The similarity search is performed on descriptor arrays by computing the distance between the query descriptor compared with reference descriptors extracted offline. The key contributions of the approach are the high accuracy, the time-effectiveness and the scalability of the method towards large image datasets. The developed method is first, integrated on a mobile platform and, then, deployed on a client-server architecture to deal with high volume image galleries. Experiments are performed to evaluate the performances of the system in real-life environment conditions and the obtained results demonstrate the relevance of the proposed approach.
U2 - 10.1109/ICSIPA.2015.7412189
DO - 10.1109/ICSIPA.2015.7412189
M3 - Conference contribution
AN - SCOPUS:84971671977
T3 - IEEE 2015 International Conference on Signal and Image Processing Applications, ICSIPA 2015 - Proceedings
SP - 197
EP - 202
BT - IEEE 2015 International Conference on Signal and Image Processing Applications, ICSIPA 2015 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 4th IEEE International Conference on Signal and Image Processing Applications, ICSIPA 2015
Y2 - 19 October 2015 through 21 October 2015
ER -