Abstract: An autofocus method includes acquiring an image of a scene that includes one or more out of focus faces and/or partial faces. The method includes detecting one or more of the out of focus faces and/or partial faces within the digital image by applying one or more sets of classifiers trained on faces that are out of focus. One or more sizes of the one of more respective out of focus faces and/or partial faces is/are determined within the digital image. One or more respective depths is/are determined to the one or more out of focus faces and/or partial faces based on the one or more sizes of the one of more faces and/or partial faces within the digital image. One or more respective focus positions of the lens is/are adjusted to focus approximately at the determined one or more respective depths.

Abstract: A method for red-eye detection in an acquired digital image acquiring one or more preview or other reference images without a flash. Any red regions that exist within the one or more reference images are determined. A main image is acquired with a flash of approximately a same scene as the one or more reference images. The main image is analyzed to determine any candidate red eye defect regions that exist within the main image. Any red regions determined to exist within the one or more reference images are compared with any candidate red eye defect regions determined to exist within the main image. Any candidate red eye defect regions within the main image corresponding to red regions determined also to exist within the one or more reference images are removed as candidate red eye defect regions.

Abstract: A method for digital image eye artifact detection and correction include identifying one or more candidate red-eye defect regions in an acquired image. For one or more candidate red-eye regions, a seed pixels and/or a region of pixels having a high intensity value in the vicinity of the candidate red-eye region is identified. The shape, roundness or other eye-related characteristic of a combined hybrid region including the candidate red-eye region and the region of high intensity pixels is analyzed. Based on the analysis of the eye-related characteristic of the combined hybrid region, it is determined whether to apply flash artifact correction, including red eye correction of the candidate red-eye region and/or correction of the region of high intensity pixels.

Abstract: A digital image acquisition device is for acquiring digital images including one or more preview images. A face detector analyzes the one or more preview images to ascertain information relating to candidate face regions therein. A speed-optimized filter produces a first set of candidate red-eye regions based on the candidate face region information provided by the face detector.

Abstract: A method for red-eye detection in an acquired digital image includes acquiring a first image, and analyzing one or more partial face regions within the first image. One or more characteristics of the first image are determined. One or more corrective processes are identified including red eye correction that can be beneficially applied to the first image according to the one or more characteristics. The one or more corrective processes are applied to the first image.

Abstract: A portable digital image acquisition device includes multiple lenses and/or multiple flashes. A main digital image and first and second reference images are acquired. The first and second reference images are acquired with different flash-lens combinations that have different flash-lens distances. One or more flash eye defects are detected and corrected in the main image based on analysis of the first and second reference images.

Abstract: A portable digital image acquisition device includes multiple lenses and/or multiple flashes. A main digital image and first and second reference images are acquired. The first and second reference images are acquired with different flash-lens combinations that have different flash-lens distances. One or more flash eye defects are detected and corrected in the main image based on analysis of the first and second reference images.

Abstract: A method for red-eye detection in an acquired digital image includes acquiring a first image, and analyzing one or more partial face regions within the first image. One or more characteristics of the first image are determined. One or more corrective processes are identified including red eye correction that can be beneficially applied to the first image according to the one or more characteristics. The one or more corrective processes are applied to the first image.

Abstract: A digital image acquisition device is for acquiring digital images including one or more preview images. A face detector analyzes the one or more preview images to ascertain information relating to candidate face regions therein. A speed-optimized filter produces a first set of candidate red-eye regions based on the candidate face region information provided by the face detector.

Abstract: A digital image acquisition device is for acquiring digital images including one or more preview images. A face detector analyzes the one or more preview images to ascertain information relating to candidate face regions therein. A speed-optimized filter produces a first set of candidate red-eye regions based on the candidate face region information provided by the face detector.

Abstract: A method for red-eye detection in an acquired digital image acquiring one or more preview or other reference images without a flash. Any red regions that exist within the one or more reference images are determined. A main image is acquired with a flash of approximately a same scene as the one or more reference images. The main image is analyzed to determine any candidate red eye defect regions that exist within the main image. Any red regions determined to exist within the one or more reference images are compared with any candidate red eye defect regions determined to exist within the main image. Any candidate red eye defect regions within the main image corresponding to red regions determined also to exist within the one or more reference images are removed as candidate red eye defect regions.

Abstract: An image is acquired including a red eye defect and non red eye defect regions having a red color. An initial segmentation of candidate redeye regions is performed. A location and orientation of one or more faces within the image are determined. The candidate redeye regions are analyzed based on the determined location and orientation of the one or more faces to determine a probability that each redeye region appears at a position of an eye. Any confirmed redeye regions having at least a certain threshold probability of being a false positive are removed as candidate redeye defect regions. The remaining redeye defect regions are corrected and a red eye corrected image is generated.

Abstract: A digital image acquisition device is for acquiring digital images including one or more preview images. A face detector analyzes the one or more preview images to ascertain information relating to candidate face regions therein. A speed-optimized filter produces a first set of candidate red-eye regions based on the candidate face region information provided by the face detector.

Abstract: An image is acquired including a red eye defect and non red eye defect regions having a red color. An initial segmentation of candidate redeye regions is performed. A location and orientation of one or more faces within the image are determined. The candidate redeye regions are analyzed based on the determined location and orientation of the one or more faces to determine a probability that each redeye region appears at a position of an eye. Any confirmed redeye regions having at least a certain threshold probability of being a false positive are removed as candidate redeye defect regions. The remaining redeye defect regions are corrected and a red eye corrected image is generated.

Abstract: A digital image acquisition device is for acquiring digital images including one or more preview images. A face detector analyzes the one or more preview images to ascertain information relating to candidate face regions therein. A speed-optimized filter produces a first set of candidate red-eye regions based on the candidate face region information provided by the face detector.

Abstract: A digital image acquisition device is for acquiring digital images including one or more preview images. A face detector analyzes the one or more preview images to ascertain information relating to candidate face regions therein. A speed-optimized filter produces a first set of candidate red-eye regions based on the candidate face region information provided by the face detector.

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.

Abstract: A method for red-eye detection in an acquired digital image acquiring one or more preview or other reference images without a flash. Any red regions that exist within the one or more reference images are determined. A main image is acquired with a flash of approximately a same scene as the one or more reference images. The main image is analyzed to determine any candidate red eye defect regions that exist within the main image. Any red regions determined to exist within the one or more reference images are compared with any candidate red eye defect regions determined to exist within the main image. Any candidate red eye defect regions within the main image corresponding to red regions determined also to exist within the one or more reference images are removed as candidate red eye defect regions.

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 a plurality of 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 a chain of one 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 chain can be adapted in accordance with the plurality of characteristics; and the red-eye filter is adapted accordingly.

Abstract: A digital image acquisition device is for acquiring digital images including one or more preview images. A face detector analyzes the one or more preview images to ascertain information relating to candidate face regions therein. A speed-optimized filter produces a first set of candidate red-eye regions based on the candidate face region information provided by the face detector.