I'm using CNN, RNN and OpenCV to identify people and cars within images, once I identify several images I'm cropping them and dividing them in cars and people.
I would like to group all same-looking cars and all same-looking people. What would be the best approach to do so?
I'm recollecting these images from an IP camera, so I cannot base my code in colors, because the light is not the same when is day and night. Plus the cars aren't always looking at the same direction. I guess SVM would work nice, but I would need classify some data by hand first. I'm looking for something to make clusters of similar images without a supervising method.
Would something like k-means work?