Object detection is a computer vision task that has become an integral part of many consumer applications today such as surveillance and security systems, mobile text recognition, and diagnosing diseases from MRI/CT scans. Object detection is also one of the critical components to support autonomous driving. Autonomous vehicles rely on the perception of their surroundings to ensure safe and robust driving performance. This perception system uses object detection algorithms to accurately determine objects such as pedestrians, vehicles, traffic signs, and barriers in the vehicle's vicinity. Deep learning-based object detectors play a vital role in finding and localizing these objects in real-time. This article discusses the state-of-the-art in object detectors and open challenges for their integration into autonomous vehicles.
翻译:物体探测是一项计算机视觉任务,已成为当今许多消费者应用软件的组成部分,例如监视和安全系统、移动文本识别和通过磁共振/CT扫描诊断疾病;物体探测也是支持自主驾驶的关键组成部分之一;自主车辆依靠对周围环境的看法来确保安全和稳健的驾驶性能;该感知系统使用物体探测算法准确确定行人、车辆、交通标志和车辆附近障碍等物体;深层学习物体探测器在实时发现和定位这些物体方面发挥着至关重要的作用;该文章讨论了物体探测器的最新状况以及将其纳入自主车辆的公开挑战。