17. The computer program product of claim 13 , wherein the method further comprises: visually indicating, in response to the identifying, the location of the zero or more objects.
13. A computer program product for detecting objects in a digital image, the computer program product comprising: a non-transitory storage medium readable by a processing circuit and storing instructions for execution by the processing circuit for performing a method comprising: receiving at least one image representing at least one frame of a video sequence comprising zero or more objects of at least one desired object type; placing a sliding window of different window sizes at different locations in the at least one image; applying, for each window size and each location, a cascaded classifier comprising a plurality of increasingly accurate layers, each layer comprising a plurality of classifiers; evaluating, at each layer in the plurality of increasingly accurate layers, an area of the at least one image within a current sliding window using one or more weak classifiers in the plurality of classifiers based on at least one of Haar features and Histograms of Oriented Gradients (HOG) features, wherein an output of each weak classifier is a weak decision as to whether the area of the at least one image within the current sliding window comprises an instance of an object of the desired object type; identifying, based on the evaluating, a location within the image of the zero or more objects associated with the desired object type; and training each weak classifier in the plurality of classifiers based on Haar features and HOG features, wherein a selection of a subsequent weak classifier during the training is based on the subsequent weak classifier that provides a strongest separation between desired target objects than other available weak classifiers independent of the subsequent weak classifier being associated with one or a Haar feature and a HOG feature.