Anchor-free one-stage detector for unmanned aerial vehicle

Haihan Li; Qiang Zhang; Wenchao Zhao; Wenming Yang; Qingmin Liao

doi:10.1117/12.2572966

12 June 2020 Anchor-free one-stage detector for unmanned aerial vehicle

Haihan Li, Qiang Zhang, Wenchao Zhao, Wenming Yang, Qingmin Liao

Proceedings Volume 11519, Twelfth International Conference on Digital Image Processing (ICDIP 2020); 1151906 (2020) https://doi.org/10.1117/12.2572966
Event: Twelfth International Conference on Digital Image Processing, 2020, Osaka, Japan

Abstract

With the popularity of commercial unmanned aerial vehicles (UAVs), people have easy access to UAV. However, people’s privacy and safety can be threatened if UAV flies at airports, private yards, etc. It is important to be able to detect the illegal UAV accurately and promptly on these vulnerable sites. However, motion blur, occlusion and truncation occur frequently due to fast movement of UAV. It is hard to make correct predictions because of the small size of UAV in images. In this paper, we propose an anchor-free one-stage method for UAV detection. The method eliminates the anchor boxes that are used in most existing detectors, which makes our method simpler and more efficient. We improve the detection accuracy in the following two ways. First, a new multi-scale feature fusion method is proposed to enhance the semantic information exchange between different scales. Second, a reasonable loss function is adopted to increase the proportion of small UAV’s loss. Experimental results validate the effectiveness of our improvements and our proposed detector achieve a superior performance.

Citation Download Citation

Haihan Li, Qiang Zhang, Wenchao Zhao, Wenming Yang, and Qingmin Liao "Anchor-free one-stage detector for unmanned aerial vehicle", Proc. SPIE 11519, Twelfth International Conference on Digital Image Processing (ICDIP 2020), 1151906 (12 June 2020); https://doi.org/10.1117/12.2572966

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