Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Aerial Vehicle Tracking by Adaptive Fusion of Hyperspectral Likelihood
  Maps   Hyperspectral cameras can provide unique spectral signatures for consistently
distinguishing materials that can be used to solve surveillance tasks. In this
paper, we propose a novel real-time hyperspectral likelihood maps-aided
tracking method (HLT) inspired by an adaptive hyperspectral sensor. A moving
object tracking system generally consists of registration, object detection,
and tracking modules. We focus on the target detection part and remove the
necessity to build any offline classifiers and tune a large amount of
hyperparameters, instead learning a generative target model in an online manner
for hyperspectral channels ranging from visible to infrared wavelengths. The
key idea is that, our adaptive fusion method can combine likelihood maps from
multiple bands of hyperspectral imagery into one single more distinctive
representation increasing the margin between mean value of foreground and
background pixels in the fused map. Experimental results show that the HLT not
only outperforms all established fusion methods but is on par with the current
state-of-the-art hyperspectral target tracking frameworks.

6
The categories of this paper are: astro-ph
24
The categories of this paper are: dg-ga
4
The categories of this paper are: cond-mat
0
The categories of this paper are: hep-ph
35
The categories of this paper are: mtrl-th
30
The categories of this paper are: q-alg
7
The categories of this paper are: hep-th
11
The categories of this paper are: hep-lat
10
The categories of this paper are: q-bio
25
The categories of this paper are: patt-sol
19
The categories of this paper are: eess
16
The categories of this paper are: stat
37
The categories of this paper are: supr-con
2
The categories of this paper are: math
22
The categories of this paper are: chao-dyn
36
The categories of this paper are: cmp-lg