Integrated Compressed Sensing and YOLOv4 for Application in Image-storage and Object-recognition of Dashboard Camera

This paper focuses on the research of the dashboard camera for improving the storage space and object recognition. The experiments showed that the CS method of ISTA-Net (Iterative Shrinkage Thresholding Algorithm with Network) can reduce the storage space by at least 60% and without obviously sacrificing the image quality. Furthermore, the recognition method by YOLOv4 can overcome the variety of environments, which can reach the recognition ratio of over 80% in a small 480x480 pixels. The recognition function can help to quickly catch the key features (ex: car, traffic signal, pedestrian, etc.) in the storage data of the dashboard camera.