Supervisor:
Southwest Ordnance Industry Bureau
Organizer:
Chongqing Ordnance Industry Society
Chongqing University of Technology
Chongqing University of Technology
Detection and behavior prediction of living aims based on human skeleton points
| DOI: | 10.11809/bqzbgcxb2025.01.029 |
| Keywords: | unmanned combat platform; living aim; human skeleton points; pose estimation; behavior estimation |
| Abstract: | In order to solve the problem in accurately judging the presence and threat level of living aims on unmanned combat platforms in complex battlefields, based on HRNet and the evaluation of human skeleton point detection models, a relay supervision mechanism is added, and an improved channel pruning methods are proposed, to achieve fast and accurate detection of living aims. Then, pose estimates for each target in multi objective scenes are obtained by a skeleton point combination method of top down approach. Human pose data under typical actions are collected, and trained behavior classifiers using multi layer perceptron and radial basis kernel support vector machine, and are verified by experimentations. The results show that the detection accuracy and inference speed of living targets have been improved, and the accuracy of behavior estimation is more than 95%. |
| Issue: | Vol. 46 No. 1 (2025) |
| Published: | 2025-01-31 |