Hello Rodrigo, copy-pasting my response from OpenCV user group. 

I think it is a great initiative and I am looking forward to see such a framework. OpenCV has a lot of infrastructure on object detection that you might want to look at, such as cascade classifier training, several machine learning classifiers and feature extraction methods. I really want to see OpenCV as a library that makes it easy to create an object detection application. OpenCV 2.2 will have some of what you call "install, run, see the graphs coming out" functionality such as a sample running bag-of-words object class detection on PASCAL VOC datasets. This framework can be used for generic object detector training too (PASCAL data structures + OpenCV methods for reading them). 

Having said that, I have to admit that OpenCV does not have a generic framework for training a detector for any type of object. And here is why: the problem is not solved yet. There are a few problems that are solved up to quality accepted by industry, face detection is one of the famous. If you look at the ROC curves from PASCAL VOC papers, a lot of them are far on the research side. OpenCV 2.2 will have two methods for detecting object classes: latent SVM and color descriptors with bag of words. Even if we try now to join them into a single framework, this will be quite hard -- the algorithms are too different. But since this is still a research problem, both approaches might change a lot over a couple of years and this will render our efforts useless. 

So my suggestion is to select the bits and pieces of object detection that are likely to survive and implement a framework for them. I already mentioned VOC datasets -- it is very important to have a data structure definition to work with. Local descriptors will be put in such a framework in OpenCV 2.2, this is a good example of "stable" functionality in my opinion.

Best Regards, Victor

On Nov 22, 2010, at 12:09 AM, Rodrigo Benenson wrote:

Hello all.

    I'm contacting you because I am considering starting a new open source project to solve a specific problem: training and evaluating objects detection algorithms.

    Hundreds of students have been there before: "I want to create a program that detects objects in images".
    They choose a dataset for training (e.g. INRIA pedestrians), a feature descriptor (e.g. HOG), a machine learning method (e.g. linear SVM), and then, they write the code to get it all together.

    In the best case they will take bits and pieces from multiple places and spend a few weeks on the glue code. In the worst case they will spend months reimplementing existing methods.

    It is time to stop the madness.
    Training detectors for objects detection in images is a specific and well defined problem.
    It is time to share our effort and build a reference open source tool to solve this common problem.
    We should have an open source tool that provides all the common bits, the glue and allows us to focus on what we really care: the algorithms.

    In some sense OpenCv 2.2 helps a lot to the task, however OpenCv is aimed to be a generic library not a specific application framework. In that sense it will never provide the desired "install, run, see the graphs coming out" experience.

    Also ROS.org helps a lot the task, by providing a generic framework to create and exchange software modules, along with standard tools for messages passing, data storage and exploration. However this framework by itself has a non negligible learning curve and it is unfamiliar to anyone outside the robotics community.


    I currently have my own idea of how things could be. However before creating "yet one more framework" I would like to have your input on the topic.

    I have created a short form to collect your opinions. I would be very glad if you could help me go in the right direction by giving your input.

    https://spreadsheets.google.com/viewform?formkey=dFFzaDlLM1liVGNOS2FENnhrc1VWckE6MQ

    The form is anonymous and the results are public.

    Based your opinions and ideas I will do my best to move forward an usable open source solution.
    Further information will be posted at
    https://wave.google.com/wave/waveref/googlewave.com/w+yH-HOCb6H

    Best regards,
    rodrigo benenson phd.

    ps: If you are interested do not hesitate to send me a message. You can contact me via github as "rodrigob". 

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