Detection and Classification of Finer-Grained Human Activities Based on Stepped-Frequency Continuous-Wave Through-Wall Radar
The through-wall detection and classification of human activities are critical for anti-terrorism, security, and disaster rescue operations. An effective through-wall detection and classification technology is proposed for finer-grained human activities such as piaffe, picking up an object, waving,...
Main Authors: | Fugui Qi, Fulai Liang, Hao Lv, Chuantao Li, Fuming Chen, Jianqi Wang |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2016-06-01
|
Series: | Sensors |
Subjects: | |
Online Access: | http://www.mdpi.com/1424-8220/16/6/885 |
Similar Items
-
MHHT-Based Method for Analysis of Micro-Doppler Signatures for Human Finer-Grained Activity Using Through-Wall SFCW Radar
by: Fugui Qi, et al.
Published: (2017-03-01) -
Real-Time Through-Wall Situation Awareness Using a Microwave Doppler Radar Sensor
by: Gianluca Gennarelli, et al.
Published: (2016-07-01) -
Extraction and Analysis of Finer Impervious Surface Classes in Urban Area
by: Wenyue Liao, et al.
Published: (2021-01-01) -
Analyzing Urban Human Mobility Patterns through a Thematic Model at a Finer Scale
by: Faming Zhang, et al.
Published: (2016-06-01) -
WFNet: A Wider and Finer Network for Salient Object Detection
by: Jun Cen, et al.
Published: (2020-01-01)