摘要
设计并实现了NVIDIA嵌入式平台Jetson TX2上的车辆跟踪系统。从摄像头采集YUV420格式的视频数据,然后将数据送到Tegra Parker硬件HEVC编码器进行编码,输出码流经过RTP封装后通过UDP广播发送,利用Gstreamer多媒体框架开发接收及解码程序,最后,针对获取的视频动态进行车辆的跟踪与显示。运行Yolo V2检测算法,对车辆进行检测,从而为跟踪系统提供跟踪对象。利用Kalman滤波算法对车辆的位置进行预测,再经过Meanshift算法进行车辆跟踪。系统能够实现帧率为60 f/s的超高清4K视频实时编码和传输,此系统中的HEVC硬件编码器编码速率比PC端x265编码器大3个数量级,PSNR比PC端x265编码器高6 dB,更加适用于智能交通中。
The vehicle tracking system on NVIDIA embedded platform Jetson TX2 is designed.Video data in YUV420 format was collected from the onboard camera and sent to the Tegra Parker hardware HEVC encoder for encoding.The output stream is encapsulated by RTP and sent by UDP broadcast.Gstreamer multimedia framework is used to develop the receiving and decoding program.Finally,the acquired video is tracked and displayed dynamically.The Yolo V2 detection algorithm is used to detect the vehicle to provide tracking objects for the tracking system.Using Meanshift method can track the detected vehicles more accurately,and adding Kalman filtering algorithm can predict the position of the target model in the current frame.The system can realize real-time encoding and transmission of ultra-high definition 4K video with frame rate of 60 f/s.The HEVC hardware encoder encoding rate in this system is three orders of magnitude larger than the PC end x265 encoder,and the PSNR is 6 dB higher than the PC end x265 encoder.It′s more suitable for intelligent transportation.
作者
张雷
王越
Zhang Lei;Wang Yue(College of Electronic Information Engineering,Shenyang Aerospace University,Shenyang 110136,China)
出处
《电子技术应用》
2019年第11期13-16,共4页
Application of Electronic Technique
