With the rapid development of drones, many problems have arisen, such as invasion of privacy and endangering security. Inspired by biology, in order to achieve effective detection and robust tracking of small targets such as unmanned aerial vehicles, a binocular vision detection system is designed. The system is composed of long focus and wide-angle dual cameras, servo pan tilt, and dual processors for detecting and identifying targets. In view of the shortcomings of spatio-temporal context target tracking algorithm that cannot adapt to scale transformation and easy to track failure in complex scenes, the scale filter and loss criterion are introduced to make an improvement. Qualitative and quantitative experiments show that the designed system can adapt to the scale changes and partial occlusion conditions in the detection, and meets the real-time requirements. The hardware system and algorithm both have reference value for the application of anti-unmanned aerial vehicle systems.

随着无人机的快速发展，出现了许多问题，例如侵犯隐私和危及安全。受生物学启发，为了实现对诸如无人机等小型目标的有效检测和鲁棒跟踪，设计了一种双目视觉检测系统。该系统由长焦距和广角双摄像头，伺服云台倾斜以及用于检测和识别目标的双处理器组成。针对时空上下文目标跟踪算法不能适应尺度变换，在复杂场景下容易跟踪失败的缺点，引入尺度过滤和损失准则进行改进。定性和定量实验表明，所设计的系统能够适应检测中尺度变化和部分遮挡条件，并满足实时性要求。硬件系统和算法均对反无人机系统的应用具有参考价值。