TY - GEN
T1 - Scale-invariant feature extraction by VQ-based local image descriptor
AU - Chen, Qiu
AU - Kotani, Koji
AU - Lee, Feifei
AU - Ohmi, Tadahiro
PY - 2008/12/1
Y1 - 2008/12/1
N2 - SIFT (Scale Invariant Feature Transform) feature is identified as being invariant to common image deformations caused by the rotation, scaling, and illumination. In this paper, instead of using SIFT's smoothed weighted orientation histograms, we apply vector quantization (VQ) histogram as an alternate representation for local image descriptor. Experimental results demonstrate that the VQ-based local descriptors are more robust to image deformations.
AB - SIFT (Scale Invariant Feature Transform) feature is identified as being invariant to common image deformations caused by the rotation, scaling, and illumination. In this paper, instead of using SIFT's smoothed weighted orientation histograms, we apply vector quantization (VQ) histogram as an alternate representation for local image descriptor. Experimental results demonstrate that the VQ-based local descriptors are more robust to image deformations.
UR - http://www.scopus.com/inward/record.url?scp=70449578241&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=70449578241&partnerID=8YFLogxK
U2 - 10.1109/CIMCA.2008.134
DO - 10.1109/CIMCA.2008.134
M3 - Conference contribution
AN - SCOPUS:70449578241
SN - 9780769535142
T3 - 2008 International Conference on Computational Intelligence for Modelling Control and Automation, CIMCA 2008
SP - 1217
EP - 1222
BT - 2008 International Conference on Computational Intelligence for Modelling Control and Automation, CIMCA 2008
T2 - 2008 International Conference on Computational Intelligence for Modelling Control and Automation, CIMCA 2008
Y2 - 10 December 2008 through 12 December 2008
ER -