17. The method as recited in claim 1 , wherein the post-filter stage further includes a masking processing.
1. A method for use in detecting faces within a digital image, the method comprising: processing via a processor, in a pre-filter stage, a set of digital image data to produce a set of initial candidate portions using at least one feature algorithm, the pre-filter stage including a linear filter based on a decision function having coefficients that are determined during a learning procedure; processing via the processor, in a boosting filter stage, the set of initial candidate portions to produce a set of intermediate candidate portions, the boosting filter stage including: a boosting chain having a plurality of boosting chain nodes to identify candidate portions and a boot strap function following each of the plurality of boosting chain nodes, the boot strap function to use a weak learner of a previous boosting chain node in training another boosting chain node of the boosting chain, wherein the weak learner includes building a simple decision stump on a histogram of a Haar-like feature on a training set; and processing via the processor, the set of intermediate candidate portions in a post-filter stage to produce a set of final candidate portions, wherein the post-filter stage includes an image pre-processing process, a color-filter process, and a support vector machine (SVM) filter process.