Abstract: A database of faceprint data corresponding to detected face regions within images acquired with an image acquisition device and digitally-embedded within one or more digital storage media includes image, identity and face recognition data components. The image data component include acquired digital image data including content data and unique identifiers corresponding to individual acquired digital images or face regions therein, or both. The identity data component includes an identification listing of known identities to which identified face regions detected within the image data have been determined to correspond. The face recognition data component includes, for an individual known identity, one or more identity tables corresponding to one or more identity entries, and one or more face class tables corresponding to one or more face class entries of the one or more identity tables.

Abstract: An image processing apparatus for tracking faces in an image stream iteratively receives a new acquired image from the image stream, the image potentially including one or more face regions. The acquired image is sub-sampled (112) 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 (20) 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 at which a next acquired image is sub-sampled is adjusted.

Abstract: A method of processing a digital image using face detection within the image achieves one or more desired image processing parameters. A group of pixels is identified that correspond to an image of a face within the digital image. Default values are determined of one or more parameters of at least some portion of the digital image. Values are adjusted of the one or more parameters within the digitally-detected image based upon an analysis of the digital image including the image of the face and the default values.

Abstract: A method for detecting a face in a mid-shot digital image of a person comprises capturing first and second mid-shot digital images of nominally the same scene using different capture settings such that the foreground is differently differentiated from the background in each image, and comparing the first and second images to determine the foreground region of the images. A portion of the foreground region likely to correspond to a face is estimated based upon the geometry of the foreground region.

Abstract: A processor-based system operating according to digitally-embedded programming instructions includes a face detection module for identifying face regions within digital images. A normalization module generates a normalized version of the face region. A face recognition module automatically extracts a set of face classifier parameter values from the normalized face region that are referred to as a faceprint. A workflow module automatically compares the extracted faceprint to a database of archived faceprints previously determined to correspond to known identities. The workflow module determines based on the comparing whether the new faceprint corresponds to any of the known identities, and associates the new faceprint and normalized face region with a new or known identity within a database. A database module serves to archive data corresponding to the new faceprint and its associated parent image according to the associating by the workflow module within one or more digital data storage media.

Abstract: A method of automatically establishing the correct orientation of an image using facial information. This method is based on the exploitation of the inherent property of image recognition algorithms in general and face detection in particular, where the recognition is based on criteria that is highly orientation sensitive. By applying a detection algorithm to images in various orientations, or alternatively by rotating the classifiers, and comparing the number of successful faces that are detected in each orientation, one may conclude as to the most likely correct orientation. Such method can be implemented as an automated method or a semi automatic method to guide users in viewing, capturing or printing of images.

Abstract: A method of modifying the viewing parameters of digital images using image feature detection for achieving desired parameters based on one or more sub-groups of pixels that correspond to one or more selected image features such as a face, body, pets, or a background region or a foreground region. Such methods may be used for animating still images, automating and streamlining application such as the creation of slide shows and screen savers of images containing selected image features. Two or more features such as a foreground region and a background region may be separated and independently processed.

Abstract: A processor-based system operating according to digitally-embedded programming instructions includes a face detection module for identifying face regions within digital images. A normalization module generates a normalized version of the face region. A face recognition module extracts a set of face classifier parameter values from the normalized face region that are referred to as a faceprint. A workflow module compares the extracted faceprint to a database of archived faceprints previously determined to correspond to known identities. The workflow module determines based on the comparing whether the new faceprint corresponds to any of the known identities, and associates the new faceprint and normalized face region with a new or known identity within a database. A database module serves to archive data corresponding to the new faceprint and its associated parent image according to the associating by the workflow module within one or more digital data storage media.

Abstract: A color filter enhancement method for a portable digital image acquisition device includes digitally exposing color pixels of a color sensor array for a first digital exposure duration and digitally exposing white pixels of a color sensor array for a second digital exposure time shorter than the first digital exposure duration. A color filter enhanced digital image is generated using data from both the color pixels exposed for the first digital exposure duration and the white pixels exposed for the second digital exposure duration.

Abstract: A processor-based system operating according to digitally-embedded programming instructions includes a face detection module for identifying face regions within digital images. A normalization module generates a normalized version of the face region that is at least pose normalized. A face recognition module extracts a set of face classifier parameter values from the normalized face region that are referred to as a faceprint. A workflow module compares the extracted faceprint to a database of archived faceprints previously determined to correspond to known identities. The workflow module determines based on the comparing whether the new faceprint corresponds to any of the known identities, and associates the new faceprint and normalized face region with a new or known identity within a database. A database module serves to archive data corresponding to the new faceprint and its associated parent image according to the associating by the workflow module within one or more digital data storage media.

Abstract: An unsatisfactory scene is disqualified as an image acquisition control for a camera. An image is acquired. One or more regions of facial or other key features are determined in the image. These regions are analyzed to determine whether they are unsatisfactorily blocked or shadowed, and if so, then the scene is disqualified as a candidate for a processed, permanent image while the feature continues to be blocked or shadowed.

Abstract: A processor-based system operating according to digitally-embedded programming instructions includes a face detection module for identifying face regions within digital images. A normalization module generates a normalized version of the face region. A face recognition module extracts a set of face classifier parameter values from the normalized face region that are referred to as a faceprint. A workflow module compares the extracted faceprint to a database of archived faceprints previously determined to correspond to known identities. The workflow module determines based on the comparing whether the new faceprint corresponds to any of the known identities, and associates the new faceprint and normalized face region with a new or known identity within a database. The archived faceprints are digitally organized and may be selectively recalled along with their associated parent images.

Abstract: Flash image orb artifacts arising from specular reflections from airborne particles are corrected. An image of a scene using flash illumination and a reference image of substantially the same scene are acquired. The reference and flash images are subtracted to generate a difference image. Edge and interior region features of an orb artifact within the difference image are determined. The edge feature is matched with the interior region, and the orb artifact is corrected from the flash image based on the matching.

Abstract: A method of automatically correcting dust artifact within images acquired by a system including a digital camera includes determining that certain pixels correspond to dust artifact regions within a first digitally-acquired image. The dust artifact regions are associated with one or more extracted parameters relating to a variable optical system of the digital camera when the first image was acquired. An associated statistical dust map is formed including mapped dust regions based on known correspondence between effects on dust artifact data of values of extracted parameters. Pixels corresponding to correlated dust artifact regions within a second image acquired with said digital camera are corrected according to one or more different values of the extracted parameters relating to the variable optical system based on the associated statistical dust map.

Abstract: A method of adjustable spatial and/or temporal compression of an image including a face includes identifying a group of pixels that correspond to a face within a digitally-acquired image. A first compression portion of the image including the group of pixels is determined. A second compression portion of the image other than the group of pixels is also determined. The first compression portion may be automatically compressed with higher-grade compression than the second compression portion to generate a compressed image including the face, or an option to provided the compressed image including the different grade compressions may be provided.

Abstract: A method automatically corrects dust artifact within images acquired by a system including a digital acquisition device including a lens assembly. Multiple original digital images are acquired with the digital acquisition device. Probabilities that certain pixels correspond to dust artifact regions within the images are determined based at least in part on a comparison of suspected dust artifact regions within two or more of the images. Probable dust artifact regions are associated with extracted parameter values relating to the lens assembly when the images were acquired. A statistical dust map is formed including mapped dust regions based on the determining and associating. Pixels corresponding to correlated dust artifact regions are corrected within further digitally-acquired images based on the associated statistical dust map.

Abstract: A method of automatically correcting dust artifact within images acquired by a system including a digital camera includes determining probabilities of dust artifact regions corresponding to pixels within a digitally-acquired image based at least in part on a pixel analysis of the region in view of predetermined characteristics indicative of the presence of a dust artifact region. The dust artifact regions are associated with one or more extracted parameters relating to the optical system when the image was acquired. A statistical dust map is formed including mapped dust regions based on the dust artifact determining and associating operations. Digital data is corrected corresponding to correlated dust artifact regions within the acquired image based on the associated statistical dust map.

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: A method for detecting a redeye defect in a digital image containing an eye comprises converting the digital image into an intensity image, and segmenting the intensity image into segments each having a local intensity maximum. Separately, the original digital image is thresholded to identify regions of relatively high intensity and a size falling within a predetermined range. Of these, a region is selected having substantially the highest average intensity, and those segments from the segmentation of the intensity image whose maxima are located in the selected region are identified.

Abstract: A system is provided for projecting a calibrated image. The system includes a projector to project an uncalibrated image. A processor-based digital image acquisition device is in communication with the projector and is disposed to acquire the projected, uncalibrated image. The device is also programmed to compensate for one or more parameters of viewing quality, and to communicate calibration information to the projector to project a first calibrated image.