I want to determine the similarity between images based on different features. The images show the same type of object (e.g. cars). I want to order images based on their similarity (e.g. through a feature vector). There are ways to solve this, for example a convolutional neural network. However, the images may be taken from slightly different perspectives: Sometimes directly from the front, sometimes with a slight ankle. What I DONT want is images ordered by their perspective rather than by the actual object. My questions:
- What can I do to avoid primary order by perspective
- Do I have to expect the ankle of the picture to be a primary factor in sorting order or will it more likely be negligible?
- Is there a way to extract/visualise the features the network uses (unsupervised) in order to manipulate the sorting order (e.g. by saying I want to increase the weight of THIS visual feature when ordering)?