Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Long-Range Gesture Recognition Using Millimeter Wave Radar   Millimeter wave (mmWave) based gesture recognition technology provides a good
human computer interaction (HCI) experience. Prior works focus on the
close-range gesture recognition, but fall short in range extension, i.e., they
are unable to recognize gestures more than one meter away from considerable
noise motions. In this paper, we design a long-range gesture recognition model
which utilizes a novel data processing method and a customized artificial
Convolutional Neural Network (CNN). Firstly, we break down gestures into
multiple reflection points and extract their spatial-temporal features which
depict gesture details. Secondly, we design a CNN to learn changing patterns of
extracted features respectively and output the recognition result. We
thoroughly evaluate our proposed system by implementing on a commodity mmWave
radar. Besides, we also provide more extensive assessments to demonstrate that
the proposed system is practical in several real-world scenarios.

11
The categories of this paper are: hep-lat
35
The categories of this paper are: mtrl-th
21
The categories of this paper are: adap-org
23
The categories of this paper are: solv-int
8
The categories of this paper are: hep-ex
26
The categories of this paper are: bayes-an
33
The categories of this paper are: plasm-ph
28
The categories of this paper are: alg-geom
34
The categories of this paper are: chem-ph
9
The categories of this paper are: nlin
10
The categories of this paper are: q-bio
36
The categories of this paper are: cmp-lg
12
The categories of this paper are: nucl-th
3
The categories of this paper are: physics
29
The categories of this paper are: funct-an
5
The categories of this paper are: gr-qc