Abstract: 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.
Abstract: The advancement of smartphones, wireless
networking and Near Field Communication (NFC) technology have
opened up a new approach to indoor navigation. Although NFC
technology has been used to support electronic commerce, access
control, and ticketing, there is a lack of research work on building
NFC-based indoor navigation system for smartphone users. This
paper presents an indoor interactive navigation system (named
I2Navi) based on NFC technology for users to navigate within a
building with ease using their smartphones. The I2Navi system has
been implemented at the Faculty of Engineering (FOE), Multimedia
University (MMU) to enable students, parents, visitors who own
NFC-enabled Android smartphones to navigate themselves within the
faculty. An evaluation is carried out and the results show positive
response to the proposed indoor navigation system using NFC and
smartphone technologies.