Using infrared HOG-based pedestrian detection for outdoor autonomous searching UAV with embedded system

Yanhua Shao; Yanying Mei; Hongyu Chu; Zhiyuan Chang; Yuxuan He; Huayi Zhan

doi:10.1117/12.2304530

10 April 2018 Using infrared HOG-based pedestrian detection for outdoor autonomous searching UAV with embedded system

Yanhua Shao, Yanying Mei, Hongyu Chu, Zhiyuan Chang, Yuxuan He, Huayi Zhan

Proceedings Volume 10615, Ninth International Conference on Graphic and Image Processing (ICGIP 2017); 106153Z (2018) https://doi.org/10.1117/12.2304530
Event: Ninth International Conference on Graphic and Image Processing, 2017, Qingdao, China

Abstract

Pedestrian detection (PD) is an important application domain in computer vision and pattern recognition. Unmanned Aerial Vehicles (UAVs) have become a major field of research in recent years. In this paper, an algorithm for a robust pedestrian detection method based on the combination of the infrared HOG (IR-HOG) feature and SVM is proposed for highly complex outdoor scenarios on the basis of airborne IR image sequences from UAV. The basic flow of our application operation is as follows. Firstly, the thermal infrared imager (TAU2-336), which was installed on our Outdoor Autonomous Searching (OAS) UAV, is used for taking pictures of the designated outdoor area. Secondly, image sequences collecting and processing were accomplished by using high-performance embedded system with Samsung ODROID-XU4 and Ubuntu as the core and operating system respectively, and IR-HOG features were extracted. Finally, the SVM is used to train the pedestrian classifier. Experiment show that, our method shows promising results under complex conditions including strong noise corruption, partial occlusion etc.

Citation Download Citation

Yanhua Shao, Yanying Mei, Hongyu Chu, Zhiyuan Chang, Yuxuan He, and Huayi Zhan "Using infrared HOG-based pedestrian detection for outdoor autonomous searching UAV with embedded system", Proc. SPIE 10615, Ninth International Conference on Graphic and Image Processing (ICGIP 2017), 106153Z (10 April 2018); https://doi.org/10.1117/12.2304530

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available