A deep learning approach for dynamic object understanding using SIFT

Deep learning is a method that is very commonly used in image recognition. We use the SIFT method to extract feature points, so that the machine can detect the objects in the motion images and they can be integrated into the operation of the robot arm to judge and capture specific objects. This method is also used to detect whether the parameters of the object meet the predetermined values. It will provide a warning if the predetermined values are not met. This can be used to identify the good and defective products on the production line. In the CNN database we have trained more than 30,000 images and improved the last step of SIFT algorithm to demonstrate that our new method can achieve better accuracy.