Abstract: A technique is provided for recognizing faces in an image stream using a digital image acquisition device. A first acquired image is received from an image stream. A first face region is detected within the first acquired image having a given size and a respective location within the first acquired image. First faceprint data uniquely identifying the first face region are extracted along with first peripheral region data around the first face region. The first faceprint and peripheral region data are stored, and the first peripheral region data are associated with the first face region. The first face region is tracked until a face lock is lost. A second face region is detected within a second acquired image from the image stream. Second peripheral region data around the second face region are extracted. The second face region is identified upon matching the first and second peripheral region data.

Abstract: A method for correcting a distorted input image includes determining a local region of an image to be displayed and dividing the region into an array of rectangular tiles, each tile corresponding to a distorted tile with a non-rectangular boundary within the input image. For each tile of the local region, maximum and minimum memory address locations of successive rows of the input image sufficient to span the boundary of the distorted tile are determined. Successive rows of the distorted input from between the maximum and minimum addresses are read. Distortion of the non-rectangular portion of the distorted input image is corrected to provide a tile of a corrected output image which is stored.

Abstract: A method of detecting a face in an image includes performing face detection within a first window of the image at a first location. A confidence level is obtained from the face detection indicating a probability of the image including a face at or in the vicinity of the first location. Face detection is then performed within a second window at a second location, wherein the second location is determined based on the confidence level.

Abstract: A technique for processing a digital image uses face detection to achieve one or more desired image processing parameters. A group of pixels is identified that corresponds to a face image within the digital image. A skin tone is detected for the face image by determining one or more default color or tonal values, or combinations thereof, for the group of pixels. Values of one or more parameters are adjusted for the group of pixels that correspond to the face image based on the detected skin tone.

Abstract: Sub-regions within a face image are identified to be enhanced by applying a localized smoothing kernel to luminance data corresponding to the sub-regions of the face image. An enhanced face image is generated including an enhanced version of the face that includes certain original pixels in combination with pixels corresponding to the one or more enhanced sub-regions of the face.

Abstract: A method comprises: receiving, from a content provider, a request for information collected from users who meet one or more criteria; determining at least one particular user who meets the one or more criteria; retrieving timestream data collected for the at least one particular user; wherein the timestream data is time-stamped and associated with a history of user sessions; wherein absolute time references in the timestream data have been converted to relative time references that relate to start-times of the user sessions; determining one or more levels of privacy requested by each of the at least one particular user; processing the timestream data to ensure the one or more levels of privacy in the timestream data; generating one or more statistical datasets from the processed timestream data; determining a fee for providing the one or more statistical datasets, and determining an award for the at least one particular user.

Abstract: A representation framework is determined in a face recognition method for a first collection of facial images including at least principle component analysis (PCA) features. A representation of said first collection is stored using the representation framework. A modified representation framework is determined based on statistical properties of original facial image samples of a second collection of facial images and the stored representation of the first collection. The first and second collections are combined without using original facial image samples. A representation of the combined image collection (super-collection) is stored using the modified representation framework.

Abstract: A processor-based system operating according to digitally-embedded programming instructions performs a method including identifying a group of pixels corresponding to a face region within digital image data acquired by an image acquisition device. A set of face analysis parameter values is extracted from said face region, including a faceprint associated with the face region. First and second reference faceprints are determined for a person using reference images captured respectively in predetermined face-portrait conditions and using ambient conditions. The faceprints are analyzed to determine a baseline faceprint and a range of variability from the baseline associated with the person. Results of the analyzing are stored and used in subsequent recognition of the person in a subsequent image acquired under ambient conditions.

Abstract: A technique is provided for generating sharp, well-exposed, color images from low-light images. A series of under-exposed images is acquired. A mean image is computed and a sum image is generated each based on the series of under-exposed images. Chrominance variables of pixels of the mean image are mapped to chrominance variables of pixels of the sum image. Chrominance values of pixels within the series of under-exposed images are replaced with chrominance values of the sum image. A set of sharp, well-exposed, color images is generated based on the series of under-exposed images with replaced chrominance values.

Abstract: A digital image acquisition system having no photographic film, such as a digital camera, has a flash unit for providing illumination during image capture and a red-eye filter for detecting a region within a captured image indicative of a red-eye phenomenon, the detection being based upon a comparison of the captured image and a reference image of nominally the same scene taken without flash. In the embodiment the reference image is a preview image of lower pixel resolution than the captured image, the filter matching the pixel resolutions of the captured and reference images by up-sampling the preview image and/or sub-sampling the captured image. The filter also aligns at least portions of the captured image and reference image prior to comparison to allow for, e.g. movement in the subject.

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 method of automatically determining a need to service a digital image acquisition system including a digital camera with a lens assembly includes analyzing pixels within one or more acquired digital images according to probability determinations that such pixels correspond to blemish artifacts. It is automatically determined whether a threshold distribution of blemish artifacts is present within one or more of the digital images. A need for service is indicated when at least the threshold distribution is determined to be present.

Abstract: A method of tracking a face in a reference image stream using a digital image acquisition device includes acquiring a full resolution main image and an image stream of relatively low resolution reference images each including one or more face regions. One or more face regions are identified within two or more of the reference images. A relative movement is determined between the two or more reference images. A size and location are determined of the one or more face regions within each of the two or more reference images. Concentrated face detection is applied to at least a portion of the full resolution main image in a predicted location for candidate face regions having a predicted size as a function of the determined relative movement and the size and location of the one or more face regions within the reference images, to provide a set of candidate face regions for the main image.

Abstract: A method and apparatus for providing image processing. For one embodiment of the invention, a digital image is acquired. One or more relatively large candidate red eye defect regions are detected in at least a portion of the image. Face detection is applied to at least a portion of the image to eliminate non-face regions and one or more relatively small candidate red eye defect regions are identified in at least a portion of the image not including the eliminated non-face regions.

Abstract: A method of detecting and applying a vertical gaze direction of a face within a digital image includes analyzing one or both eyes of a face within an acquired image, including determining a degree of coverage of an eye ball by an eye lid within the digital image. Based on the determined degree of coverage of the eye ball by the eye lid, an approximate direction of vertical eye gaze is determined. A further action is selected based on the determined approximate direction of vertical eye gaze.

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 computer-implemented method for viewing images on an interactive computing device comprises displaying an image from a stack comprising a display image and at least one compressed sub-image of nominally the same scene, each of the sub-images of the stack having been acquired at respective focal distances. Responsive to a user selecting a portion of the displayed image, the selected portion is mapped to a corresponding mapped portion of a sub-image within the stack according to the difference in focal distances between the displayed image and the sub-image. At least one row of compressed image blocks of the at least one sub-image extending across the mapped portion; and a reference value for a point in the compressed image stream of the sub-image preceding the row of compressed image blocks is determined.

Abstract: Methods and systems for detecting and correcting chromatic aberration and purple fringing are disclosed. Chromatic aberration can be addressed by separating an image into color planes and then adjusting these to reduce chromatic aberration by using a specific calibration image (calibration chart) as an empirical method to calibrate the image acquisition device. Purple fringing can be corrected by initially addressing color aberration resulting from the lateral chromatic aberration (LCA). The LCA is first removed and then the correction is extended to purple fringing. A discovery is relied upon that the purple fringing is created in the direction of the chromatic aberration and is more pronounced in the direction of the chromatic aberration.

Abstract: A smart-focusing technique includes identifying an object of interest, such as a face, in a digital image. A focus-generic classifier chain is applied that is trained to match both focused and unfocused faces and/or data from a face tracking module is accepted. Multiple focus-specific classifier chains are applied, including a first chain trained to match substantially out of focus faces, and a second chain trained to match slightly out of focus faces. Focus position is rapidly adjusted using a MEMS component.

Abstract: Methods and systems for detecting and correcting chromatic aberration and purple fringing are disclosed. Chromatic aberration can be addressed by separating an image into color planes and then adjusting these to reduce chromatic aberration by using a specific calibration image (calibration chart) as an empirical method to calibrate the image acquisition device. Purple fringing can be corrected by initially addressing color aberration resulting from the lateral chromatic aberration (LCA). The LCA is first removed and then the correction is extended to purple fringing. A discovery is relied upon that the purple fringing is created in the direction of the chromatic aberration and is more pronounced in the direction of the chromatic aberration.