Tracking Small Objects at High Speed

Hi @GeekAlexis, I loved your project and included it in my studies. I’m doing vehicle tracking and calculating real-time speed among other types of analysis. As a crucial part of my project it includes Object Detection and Tracking. FastMOT is perfect for starting my project. I’ve done all Yolov4 Darknet Detection training and I’m going to do Fast-REID Training. I did some tests with aerial video images and I have some questions. I used it as Feature Extractor OSNet025, apparently it works very well.

However, small objects at high speed, the object changes its identity very often, I believe this is due to KLT optical flow tracking.

Do you have any clue as to how I can fix this?

Check Videos Output using:

detector_frame_skip = 5

and

detector_frame_skip = 1

Output Video Here

[levipereira]

Hi @GeekAlexis , Bad news… I did tons of tests using OPENCV with ffmpeg NVDEC with RTX 2060 and I could get only 65 Fps (70%GPU utilization) with 4k video while in CPU i7-8700 i got 170 FPS (100% utilization). Using only FFMPEG and NVDEC i got 220Fps. I think there is some issue between ffmpeg and opencv when using HA, because that I think is not good implement for now OPENCV with NVDEC, but I have not tested ENCODE (NVENC).

These libraries seems to be interesting.

https://docs.nvidia.com/deeplearning/dali/user-guide/docs/index.html https://docs.nvidia.com/jetson/l4t-multimedia/group__LibargusAPI.html

[levipereira]

It’s work and is fast to decode/encode, my next step is test decode and resize in gpu. This can realy help us. My dockerfile is a mess, I need clean it before send you. I’ll try build a small image with opencv and ffmpeg and gstreamer with H/W acceleration enabled