Boosted Classifier for Car Detection
نویسنده
چکیده
Recently, Viola and Jones [1] have proposed a detector using Adaboost to select and combine weak classifiers from a very large pool of weak classifiers, and it has been proven to be very successful for detecting faces. We have followed their approach and applied it to detect rear views of cars. The detector was carefully examined and was expanded in a number of ways, such as varying the type and complexity of weak learners, using Real Adaboost, fitting parametric functions to the probability distributions, aligning training images at different positions, and exploiting a tendency in the classifier to speed up the running time.
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