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: A sign pattern is a matrix whose entries belong to the set
{+,−, 0}. An n-by-n sign pattern A is said to allow an eventually
positive matrix if there exist some real matrices A with the same
sign pattern as A and a positive integer k0 such that Ak > 0 for all
k ≥ k0. It is well known that identifying and classifying the n-by-n
sign patterns that allow an eventually positive matrix are posed as two
open problems. In this article, the tree sign patterns of small order
that allow an eventually positive matrix are classified completely.