Object Detection Using Frame Difference

Robotics & Edge Computing Jetson & Embedded Systems Jetson Nano
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1

Hi all,

I’m working on object detection using frame difference. Usually, when talking about object detection, CNNs, such as SSD, RCNN, and YOLO, are used and they return accuracies and positions (x,y,w,h). However I cannot run those models due to the hardware limitation (Jetson nano and in real-time) and also find them a bit unnecessary.
(I am aware of TensorRT optimization and its benchmark)

What I want to do is,

Frame difference → cv2.findContours() or available contour algorithms → detection by using sliding window + classification (ResNet50 in TensorRT) on each contour

I managed to write my code using cv2.cuda for frame difference part, but cv2.cuda doesn’t have findContours()

Is there any alternative for cv2.findContour?

Also, I want to hear some other approaches than sliding window technique.

I want to exploit every resource of Jetson Nano.

Thank you.

3

Hi,

Unfortunately, we don’t have a CUDA API for image contour.
An alternative is to use the C++ version findContours() and inference it on TensorRT after memcpy.

Thanks.