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...
Saved in:
Main Author: | |
---|---|
Other Authors: | |
Format: | Thesis-Master by Coursework |
Language: | English |
Published: |
Nanyang Technological University
2024
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/177655 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
id |
sg-ntu-dr.10356-177655 |
---|---|
record_format |
dspace |
spelling |
sg-ntu-dr.10356-1776552024-05-31T15:50:41Z Cross-view detection of crowded objects based on multi-sensor fusion Gu, Zhipeng Wang Dan Wei School of Electrical and Electronic Engineering EDWWANG@ntu.edu.sg Engineering 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 Master's degree 2024-05-29T06:16:32Z 2024-05-29T06:16:32Z 2024 Thesis-Master by Coursework Gu, Z. (2024). Cross-view detection of crowded objects based on multi-sensor fusion. Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/177655 https://hdl.handle.net/10356/177655 en application/pdf Nanyang Technological University |
institution |
Nanyang Technological University |
building |
NTU Library |
continent |
Asia |
country |
Singapore Singapore |
content_provider |
NTU Library |
collection |
DR-NTU |
language |
English |
topic |
Engineering |
spellingShingle |
Engineering Gu, Zhipeng Cross-view detection of crowded objects based on multi-sensor fusion |
description |
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 |
author2 |
Wang Dan Wei |
author_facet |
Wang Dan Wei Gu, Zhipeng |
format |
Thesis-Master by Coursework |
author |
Gu, Zhipeng |
author_sort |
Gu, Zhipeng |
title |
Cross-view detection of crowded objects based on multi-sensor fusion |
title_short |
Cross-view detection of crowded objects based on multi-sensor fusion |
title_full |
Cross-view detection of crowded objects based on multi-sensor fusion |
title_fullStr |
Cross-view detection of crowded objects based on multi-sensor fusion |
title_full_unstemmed |
Cross-view detection of crowded objects based on multi-sensor fusion |
title_sort |
cross-view detection of crowded objects based on multi-sensor fusion |
publisher |
Nanyang Technological University |
publishDate |
2024 |
url |
https://hdl.handle.net/10356/177655 |
_version_ |
1800916428118818816 |