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Algorithms for RealTime Object Detection in Images

Real time face detection images has received growing attention recently. Recognition of other objects, such as cars, is also important. Applications are similar and content based real time image retrieval. Real time object detection in images is currently achieved by designing and applying automatic or semi-supervised machine learning algorithms. Some algorithmic solutions to these problems are reviewed. Existing real time object detection systems are based primarily on the AdaBoost framework, and the chapter will concentrate on it. Emphasis is given to approaches that build fast and reliable object recognizers in images based on small training sets. This is important in cases where the training set needs to be built manually, as in the case of detecting the back of cars, studied here as a particular example.