Design of Moving Object Detector Based on Modified GMM Algorithm for UAV Collision Avoidance

• Published in: Journal of semiconductor technology and science Vol. 18; no. 4; pp. 491 - 499
• Main Authors: Cho, Jaechan, Jung, Yongchul, Kim, Dongsun, Lee, Seongjoo, Jung, Yunho
• Format: Journal Article
• Language: English
• Published: 대한전자공학회 01.08.2018
• Subjects: 전기공학; moving object detection; UAV; Background subtraction; FPGA; Gaussian mixture model
• ISSN: 1598-1657; 2233-4866
• DOI: 10.5573/JSTS.2018.18.4.491

In this paper, we propose a moving object detection (MOD) algorithm for unmanned aerial vehicle (UAV) collision avoidance, also presenting its hardware design and implementation results. The proposed MOD algorithm is based on a modified Gaussian mixture model (GMM) based background subtraction (BS) algorithm. Typical GMM based BS algorithms show superior performance in situations where the camera is kept stationary, but their performance is significantly degraded when the camera is moving, which occurs UAV applications. Therefore, we propose a modified GMM based BS algorithm that is able to compensate for the camera ego-motion by using UAV motion information obtained from an inertial measurement unit (IMU). The proposed moving object detector was designed with Verilog-HDL, and the real-time operation was verified and evaluated using an FPGA based test system. The proposed moving object detector was implemented with 475 logic slices, 5 DSP48s, and a block memory of 3,686.4 Kbits, and it can support real-time processing at an operating frequency of 170MHz for 1280×720 HD images. KCI Citation Count: 2