%0 Journal Article
	%A Yali Zheng and  Peipei Luo and  Shinan Chen and  Jiasheng Hao and  Hong Cheng
	%D 2017
	%J International Journal of Computer and Information Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 123, 2017
	%T Visual Search Based Indoor Localization in Low Light via RGB-D Camera
	%U https://publications.waset.org/pdf/10006850
	%V 123
	%X Most of traditional visual indoor navigation algorithms
and methods only consider the localization in ordinary daytime, while
we focus on the indoor re-localization in low light in the paper. As
RGB images are degraded in low light, less discriminative infrared
and depth image pairs are taken, as the input, by RGB-D cameras, the
most similar candidates, as the output, are searched from databases
which is built in the bag-of-word framework. Epipolar constraints can
be used to relocalize the query infrared and depth image sequence.
We evaluate our method in two datasets captured by Kinect2. The
results demonstrate very promising re-localization results for indoor
navigation system in low light environments.
	%P 403 - 406