HODET：使用mmWave雷达和视觉传感器的混合目标检测和跟踪
HODET: Hybrid Object DEtection and Tracking using mmWave Radar and Visual Sensors
摘要：
图像传感器已在汽车应用中进行了大量探索，用于避免碰撞和不同程度的自主性。它需要一定程度的亮度，因此，在夜间操作或黑暗条件下使用图像传感器可能会出现问题，以及具有挑战性的天气，如雾。雷达传感器已被用来帮助覆盖可见光谱相机的各种环境挑战。边缘计算技术有可能解决许多问题，例如实时处理要求，从拥挤的服务器卸载处理，以及尺寸，重量，功率和成本（SWaP-C）限制。本文提出了一种新的混合目标检测和跟踪（HODET）使用毫米波雷达和视觉传感器的边缘。HODET是低SWaP-C电子设备的计算应用，同时使用图像和雷达传感器执行目标检测、跟踪和识别算法。虽然机器视觉摄像头可以单独估计物体的距离，但雷达传感器将提供准确的距离和运动矢量。可以利用这种额外的数据准确性来进一步区分检测到的对象，以防止欺骗攻击。选择一个真实的智能社区公共安全监控场景来验证HODET的有效性，它可以检测，跟踪感兴趣的对象并识别可疑活动。实验结果证明了该方法的可行性。
英文摘要：
Image sensors have been explored heavily in automotive applications for collision avoidance and varying levels of autonomy. It requires a degree of brightness, therefore, the use of an image sensor in nighttime operation or dark conditions can be problematic along with challenging weather such as fog. Radar sensors have been employed to help cover the various environmental challenges with visible spectrum cameras. Edge computing technology has the potential to address a number of issues such as real-time processing requirements, off-loading of processing from congested servers, and size, weight, power, and cost (SWaP-C) constraints. This paper proposes a novel Hybrid Object DEtection and Tracking (HODET) using mmWave Radar and Visual Sensors at the edge. The HODET is a computing application of low SWaP-C electronics performing object detection, tracking and identification algorithms with the simultaneous use of image and radar sensors. While the machine vision camera alone could estimate the distance of an object, the radar sensor will provide an accurate distance and vector of movement. This additional data accuracy can be leveraged to further discriminate a detected object to protect against spoofing attacks. A real-world smart community public safety monitoring scenario is selected to verify the effectiveness of HODET, which detects, tracks objects of interests and identify suspicious activities. The experimental results demonstrate the feasibility of the approach.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
