Please use this identifier to cite or link to this item:
https://hdl.handle.net/10356/71507
Title: | Visual obstacle detection for UAV | Authors: | Phua, Rui Qing | Keywords: | DRNTU::Engineering::Electrical and electronic engineering | Issue Date: | 2017 | Abstract: | The advancement in the Unmanned Aerial Vehicle (UAV) technology has resulted in the increasing usage of automatic applications, particularly with computer vision such as object and human detection. Detecting the presence of humans from a long range through an aerial view is still a challenge to-date. From the view of a UAV, humans are difficult to detect due to having only a small number of pixels. In many applications, human shadows are deemed to be a hassle in image processing and thus removed by many existing tools and algorithms. However, this project would leverage on these shadows to improve the accuracy of human detection. This report would describe and analyze three experiments that would focus on human detection without shadows, with shadows and real-time video human detection. Based on the analysis of the results obtained, it was observed that the accuracy was indeed improved with the usage of shadows. | URI: | http://hdl.handle.net/10356/71507 | Schools: | School of Electrical and Electronic Engineering | Rights: | Nanyang Technological University | Fulltext Permission: | restricted | Fulltext Availability: | With Fulltext |
Appears in Collections: | EEE Student Reports (FYP/IA/PA/PI) |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
PhuaRuiQing FYP FINAL REPORT.pdf Restricted Access | 3.44 MB | Adobe PDF | View/Open |
Page view(s)
265
Updated on Sep 25, 2023
Download(s) 50
17
Updated on Sep 25, 2023
Google ScholarTM
Check
Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.