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in my project i want to identify objects and then detect what they are(water bottle, ball, etc). I thought of identifying the objects in the image and then match that object with a object database using SURF method.

But the problem is to identify the whether my image has a object or not and how many objects are there.

I did some search and find out about "contours", a way to track shapes. I want to know whether "contours" will help to solve my problem or any other way to solve this.

Thanks.

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First, for identifying the objects you can also use BoW, cascade classifier or latent svm.

Once you have an object classifier, you can use the sliding window approach to search for the object in the image. Take a look at the cascade classifier for an example of the sliding window approach.

EDIT: here's a post blog I wrote about BoW theory and packages in Matlab and openCV http://gilscvblog.wordpress.com/2013/08/23/bag-of-words-models-for-visual-categorization/

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Hey i have tried the cascade classifier to detect object. Then it will be straight forward. So i look at the BoW method you have suggested. Can you explain a little bit about BoW. At least a good tutorial. I found some, but could not get the exact idea.
I've edited the answer to include a ling to a blog post about this subject. keep in mind that BoW is just a classifier and for detecting the object in the image, you would have to use a sliding window (or a pyramid).

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