Hello.
I have a USB camera which is connected to a linux machine. I've configured this machine to record video using ffmpeg command.
ffmpeg -f v4l2 -framerate 30 -video_size 1280x720 -input_format mjpeg -i /dev/video0 -preset faster -pix_fmt yuv420p -b 5M -t 00:01:00 out.mp4
My USB camera supports up to 30 FPS in FHD. I've also connected the USB camera to USB 3.0 ports for enabling higher data rate.
The problem is, when I load this video to a python program and run NN-based algorithm object detection (SSD+MobileNetsv2) frame by frame, moving object in the frame seems blurrier in comparison to the original video that I've recorded. There would be a lot of reasons for failing object detection from a video frame but I presume due to the blurriness it fails to detect. (Also I know that there is no perfect object detection algorithm which suits all cases)
So, could anyone give me pointers on where to adjust, so that moving objects are better detected frame by frame? 1) better quality USB webcam? 2) changing the ffmpeg command line? 3) adjust opencv cap.read()?
Thanks in advance