A Color Boosted Local Feature Extraction Method for Mobile Product Search
D. Hope (Eds.) Int. J. on Recent Trends in Engineering and Technology,, 10 (2):
7(January 2014)
Abstract
Mobile visual search is one popular and promising research area for product
search and image retrieval. We present a novel color boosted local feature extraction
method based on the SIFT descriptor, which not only maintains robustness and
repeatability to certain imaging condition variation, but also retains the salient color and
local pattern of the apparel products. The experiments demonstrate the effectiveness of our
approach, and show that the proposed method outperforms those available methods on all
tested retrieval rates.
%0 Journal Article
%1 hope2014color
%D 2014
%E Hope, Dr.Martin
%J Int. J. on Recent Trends in Engineering and Technology,
%K SIFT_color SIFT_feature extraction_mobile product search
%N 2
%P 7
%T A Color Boosted Local Feature Extraction Method for Mobile Product Search
%U http://searchdl.org/public/journals/2014/IJRTET/10/2/37.pdf
%V 10
%X Mobile visual search is one popular and promising research area for product
search and image retrieval. We present a novel color boosted local feature extraction
method based on the SIFT descriptor, which not only maintains robustness and
repeatability to certain imaging condition variation, but also retains the salient color and
local pattern of the apparel products. The experiments demonstrate the effectiveness of our
approach, and show that the proposed method outperforms those available methods on all
tested retrieval rates.
@article{hope2014color,
abstract = {Mobile visual search is one popular and promising research area for product
search and image retrieval. We present a novel color boosted local feature extraction
method based on the SIFT descriptor, which not only maintains robustness and
repeatability to certain imaging condition variation, but also retains the salient color and
local pattern of the apparel products. The experiments demonstrate the effectiveness of our
approach, and show that the proposed method outperforms those available methods on all
tested retrieval rates.},
added-at = {2014-02-01T10:44:21.000+0100},
biburl = {https://www.bibsonomy.org/bibtex/2bbd198b0ffe5828ba428ecad6315aa0e/idescitation},
editor = {Hope, Dr.Martin},
interhash = {4281ce3c784c019d52463fc23d43f61a},
intrahash = {bbd198b0ffe5828ba428ecad6315aa0e},
journal = {Int. J. on Recent Trends in Engineering and Technology,},
keywords = {SIFT_color SIFT_feature extraction_mobile product search},
month = {January},
number = 2,
pages = 7,
timestamp = {2014-02-01T10:44:21.000+0100},
title = {A Color Boosted Local Feature Extraction Method for Mobile Product Search},
url = {http://searchdl.org/public/journals/2014/IJRTET/10/2/37.pdf},
volume = 10,
year = 2014
}