I want to detect the location of a single class of object, which might occur multiple times in an image. Specifically, this relates to research on detecting brake lights for autonomous vehicles. I imagine similar techniques could be used to detect all faces for security applications, or balls for robot soccer, or a specific type of cancer or…
At the moment I am considering retraining a YOLO9000 or SSD network, as both have the necessary real-time performance to run 30fps. However, I'm assuming that at least some of their capacity is dedicated to features I don't need
- classification across a wide range of classes
- detecting whether something is an object or not for any of these classes
Since my problem is much simpler, I wondered whether there are any network architectures which have specialised on the localisation task?
I have found similar questions, but in both cases the question I want an answer to was mixed up with a secondary question and didn't give the answer I was looking for. I'd be happy to close as a dupe if one of these gets a better answer:
https://stackoverflow.com/questions/45891271/neural-network-to-detect-one-class-of-object-only
https://ai.stackexchange.com/questions/2279/cnn-for-detecting-not-just-the-nature-of-the-object-but-position-within-image-a
I did learn one helpful thing from those questions: trying to detect a single class is actually differentiating between 2 classes – objects I want to detect and background/everything else.
Best Answer
I am currently doing a single class segmentation network to detect pixels in microscopy images. What I am doing is like one step more than what you need to do.
Basically I am using FCN-8 to do pixel classification, but the first part of the model is a VGG16.
I would look online for a generic Keras or other library VGG16 model, and retrain it on your dataset.
This implies that you have a large enough dataset to train the model with and some time in front of you as they require a long training to be really accurate.
One article that might be of help: https://alexisbcook.github.io/2017/global-average-pooling-layers-for-object-localization/