Hi! I’m having issues dealing with some false positives and I would love some outside opinions!
We use 640x480 depth cams to look for trash on the ground for the robot to pickup. Detections on a single frame arent important as we wait until an object has been seen multiple sequential frames to accept it as a valid object. Right now we are trying to reduce the number of false positives and there are a couple of environmental features that are a consistent problem for us. Oil spots & painted parking lines. Oil spots are easy enough to deal with - we can make a new class for oil spots, teach the model to recognize them, and then ignore detections with the oil spot label. Parking lines are a bit trickier. It will recognize the segments of the handicap parking spot symbol as well as the end of parking spot lines. I have a couple of solutions in mind, but I would love to hear how others would approach this problem. (Non ML CV solutions also encouraged). We do a lot already to filter out false positives, and these cases are the last remaining sore spots for our model. Theres some images included below and I can provide more info if needed. -Thanks! 
