Abstract: A method for red-eye detection in an acquired digital image comprises acquiring a first image and analyzing the first acquired image to provide characteristics indicative of image quality. The process then determines if one or more corrective processes can be beneficially applied to the first acquired image according to the characteristics. Any such corrective processes are then applied to the first acquired image. Red-eye defects are then detected in a second acquired image using the corrected first acquired image. Defect detection can comprise applying one or more, or a chain of two or more, red-eye filters to the first acquired image. In this case, prior to the detecting step, it is determined if the red-eye filter or red eye filter chain can be adapted in accordance with the characteristics. The red-eye filter may be adapted accordingly.

Abstract: An image processing apparatus for tracking faces in an image stream iteratively receives an acquired image from the image stream potentially including one or more face regions. The acquired image is sub-sampled at a specified resolution to provide a sub-sampled image. An integral image is then calculated for a least a portion of the sub-sampled image. Fixed size face detection is applied to at least a portion of the integral image to provide a set of candidate face regions. Responsive to the set of candidate face regions produced and any previously detected candidate face regions, the resolution is adjusted for sub-sampling a subsequent acquired image.