Cross-view detection of crowded objects based on multi-sensor fusion
This proposal introduces a fusion detection method of color camera and LiDAR, which can achieve more ideal detection and tracking performance under limited computational resources, and explores a joint fusion detection method deployed on multiple robots, which can improve the detection performance o...
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| Format: | Thesis-Master by Coursework |
| Language: | English |
| Published: |
Nanyang Technological University
2024
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/177655 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | This proposal introduces a fusion detection method of color camera and LiDAR, which can achieve more ideal detection and tracking performance under limited computational resources, and explores a joint fusion detection method deployed on multiple robots, which can improve the detection performance of multiple robots. Traditional methods are limited by single-sensor constraints, high com putational requirements, and poor real-time performance. The proposed fusion method significantly improves detection accuracy and reliability, and solves the problem of data discrepancy and interference between sensors and robots. This approach is valuable for advancing single robots as well as multiple robots in
various applications |
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