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Classification of object from a video/Image ( human, animals, others(cars etc.,))

asked 2012-10-22 11:17:17 -0600

UserOpenCV gravatar image

Hi I am new to image processing field. My project is to classify the objects in an image/Video. The input is an image/video from surveillance camera. I should classify the objects into three classes. 1) Humans 2) Animals 3) Others (cars). We can consider a fixed background.

Can any one suggest any proven algorithms or papers or opensource code for this purpose? offcourse googling is obvious solution but always an experienced eye is always helpful!

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answered 2012-11-10 05:41:45 -0600

icedecker gravatar image

Two approaches are possible:

1 - Use of Bag of Words. Usually have four steps:

  1. Get the feature points from training data;
  2. Create a vocabulary from the features;
  3. Train (using SVM for example);
  4. Test in a image (not in training examples).

    There is a example here and in opencv/samples/cpp/bagofwords.cpp

2 - Use of a latent svm detector. The explanation is here. Have a running example of detection/categorization in opencv/samples/cpp/latentsvmdetector.cpp. You also need the opencv_extra/testdata/cv/latentsvm to properly test it. However I don't know how to make the training of new models in OpenCV.

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This question was not about NLP - but about object detection - i do not understand. I would use a pretrained object detector(model) for this.

holger gravatar imageholger ( 2020-02-20 03:51:39 -0600 )edit

answered 2012-11-09 10:32:20 -0600

insaf gravatar image


I have to do the same for my project. We can talk more about that if you want : [email protected]

See you.

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Asked: 2012-10-22 11:17:17 -0600

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Last updated: Nov 10 '12