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Show HN: OpenCV based multi-object-tracker with various object detection models

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Re: Show HN: OpenCV based multi-object-tracker with various object detection models

#21

Post by adipandas »

kevinsundar wrote: post #12
martinshen wrote: post #5

Have you tried using object attributes/features to enable tracking instead of IOU-based tracking? I suspect this tracker falls apart when there are significant obstructions. Thoughts on a Recurrent YOLO or DeepSORT based tracker?

I've found that IOU based tracking is surprisingly reliable (my dataset was primarily surveillance footage with a static camera) if you take measures to smooth the data and predict object motion using a kalman filter.

Kalman filter is also one good way to reliably keep track of objects under significant obstruction.

Re: Show HN: OpenCV based multi-object-tracker with various object detection models

#22

Post by adipandas »

alexcnwy wrote: post #19

I've built several object detection systems and you definitely want to fine-tune your model to get good results, even if the object class you want to track is available in a pre-trained model (often it isn't). For example, pre-trained models don't work too well at detecting people in surveillance footage when the camera is mounted on the ceiling and people are at an angle in the footage. Off-the-shelf object detectio…

The top-down view problem is what I was facing when I was trying to use a detection model for a project with quadcopters. For this I had to train my object detector with the data we collected from that view. YOLO was used for this work.

Yes, replacing the fine-tuned model with compiled graph should work. I tried to keep it simple and intuitive to change the model so as to allow the use of any other custom models.

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