Target video intelligent processing system based on Raspberry Pi

Abstract

In order to effectively solve the problems of insufficient storage capacity, too late to shoot wonderful moments, and limited range of shooting space, a target video intelligent processing system based on Raspberry Pi is proposed. The system runs on the Raspberry Pi, and drives the camera to shoot a wider range of indoor environment video streams through the servo gimbal. For each frame of image in the video stream, image grayscale, filter denoising and histogram, equalization techniques are used for preprocessing. In the target detection and tracking stage, first use the OpenCV machine vision library to call the MobileNet lightweight convolutional neural network and SSD algorithm combined model (MobileNetSSD) for target detection, then it can alculate the relative position of the camera center focus and the target center, and finally drive the camera to track the target object. In terms of video processing, with the help of the results obtained during target detection, the automatic video editing process is completed by discarding the image frame without target object. Experiments show that the system can quickly and accurately track the target object to shoot, and effectively reduce the storage capacity of the video.