Name
Abstract | ||
|---|---|---|
The classification of different human activities with radar has been a widely researched topic in recent years. Oftentimes, when no experimental data is available, simulated data can be exploited to test classification algorithms. Kinematic models such as the Thalmann Model and motion capture (MOCAP) data are frequently used to simulate radar signatures of human movements. While the Thalmann Model provides a model only for human walking, MOCAP data has the capability to supply data for almost any type of human activity. However, most commercial MOCAP data acquisition systems are quite expensive, making it difficult to obtain MOCAP data. In this paper, economical, easily obtainable and practical Kinect sensor is used to develop a skeleton tracking algorithm. In this way, simulated radar micro-Doppler signatures for different people and activities are computed. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/SIU.2014.6830404 | Signal Processing and Communications Applications Conference |
Keywords | Field | DocType |
Doppler radar,data acquisition,kinematics,radar tracking,Kinect sensor,MOCAP data acquisition,Thalmann model,different human activities,human movements,human walking,kinematic models,microDoppler signatures,motion capture,radar signatures,radar simulation,skeleton tracking,test classification,Kinect,human,micro-Doppler,radar,simulation | Radar,Motion capture,Computer vision,Signal processing,Data modeling,Kinematics,Pattern recognition,Experimental data,Computer science,Data acquisition,Artificial intelligence,Statistical classification | Conference |
ISSN | Citations | PageRank |
2165-0608 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Baris Eroi | 1 | 0 | 0.34 |
| Cesur Karabacak | 2 | 9 | 1.68 |
| Sevgi Zubeyde Gurbuz | 3 | 52 | 8.44 |
| Ali Cafer Gürbüz | 4 | 29 | 9.17 |