A tool which will analyse submitted images, and attempt to classify them through image recognition by manufacturer. It will be built on top of the OpenCV library.
- classifier by manufacturer
- does it need to be by model type?
- is generic Porsche (for example) classifier sufficient?
- or do need 996, 997, Cayman, Boxster etc
- separate classifiers for angle types (front, side, rear etc)
- does it need to be by model type?
- HAAR or LBP?
- LBP potentially much quicker to train?
- Which has greater accuracy for given training time?
- (LBP could be trained with more images in same time?)
- Accuracy?
- how many training images are sufficient to get >70% accuracy
- curve of accuracy… graph on time to train vs accuracy over different sized sets of prospects.
- online training of classifiers?
- take input files (image), add to queue.
- Should it take input over HTTP or direct from disk?
- initially HTTP I think, because not done it before.
- have classifier workers pull images off the queue, attempt each form of classifier in turn (most populate types first)
- worker output is:
- If single classifier matched, HTTP response with classifier that matched.
- if multiple classifiers match, then review confidence for each classifier
- respond with both along with confidence for each.
- if no classifiers match, then respond saying no match, flag for manual intervention.
- http://www.vision.ee.ethz.ch/~hegrabne/papers/Grabner2008TrainingSequentialOn-lineBoosting.pdf
- http://en.wikipedia.org/wiki/Online_machine_learning
- http://web.mit.edu/seyda/www/Papers/GHC06_ACMSRC_abstract.pdf
- http://lmb.informatik.uni-freiburg.de/papers/download/fe_za_bu_GFKL07.pdf
- http://www.svms.org/training/ChLi.pdf
- http://www.csie.ntu.edu.tw/~cjlin/papers/newsvr.pdf
- http://dsp.stackexchange.com/questions/3149/online-boosting-training-on-the-fly-for-face-detection
- http://stackoverflow.com/questions/8791178/haar-cascades-vs-lbp-cascades-in-face-detection
- http://opencv-users.1802565.n2.nabble.com/LBP-vs-haar-cascades-td7312041.html
- http://hal.inria.fr/docs/00/62/43/60/PDF/Finalversion_Haar_like_and_LBP_based_features.pdf