Closed raphaelschwinger closed 3 years ago
CSRT Tracker(OpenCV Library): Discriminative Correlation Filter Higher object tracking accuracy and can tolerate slower FPS throughput.
YOLO object detection model.
If the algorithm doesn't perform well then we can train a deep learning model for object detection or we can pick a pre-trained model and fine-tune it on our generated Blender image data.
Frame Differencing: Tracking the pixels and the coordinates of the moving object from each frame.
Image Thresholding: Preprocessing images to get better object representation. i.e: Greyscale image.
Finding Contours: Contours are used to identify the shape of an area in the image having the same color or intensity.
Image Dilation: Convolution operation on an image wherein a kernel is passed over the entire image to make features more visible.
@rxxxxxxb why do you suggest a CSRT Tracker and not e.g. KFC Tracker? I would suggest that we try out these two first.
Yes, we can try both of them.
But according to my knowledge so far, CSRT performs better with low FPS and provides higher accuracy than KCF. That's why I want to try it first.
@rxxxxxxb I added a new PR for your code https://github.com/raphaelschwinger/cone_reconstruction/pull/24.
CSRT seems to perform better then KCF in my tests as well!
Output the position of the car at each timestamp
Deliverables