Abstract: A technique of generating a panoramic image involves acquiring a set of at least two main image frames, as well as corresponding generating and/or acquiring corresponding relatively low-resolution image frames, of overlapping portions of a panoramic scene. A map or other information is stored relating to the generation of a low-res panorama. A main panorama image is formed by joining main image frames based on the map or other information gained in the low-res process.

Abstract: A technique of generating a panoramic image involves acquiring a set of at least two main image frames, as well as corresponding generating and/or acquiring corresponding relatively low-resolution image frames, of overlapping portions of a panoramic scene. A map or other information is stored relating to the generation of a low-res panorama. A main panorama image is formed by joining main image frames based on the map or other information gained in the low-res process.

Abstract: A technique of generating a panoramic image involves acquiring a set of at least two main image frames, as well as corresponding generating and/or acquiring corresponding relatively low-resolution image frames, of overlapping portions of a panoramic scene. A map or other information is stored relating to the generation of a low-res panorama. A main panorama image is formed by joining main image frames based on the map or other information gained in the low-res process.

Abstract: A technique of generating a panoramic image involves acquiring a set of at least two main image frames, as well as corresponding generating and/or acquiring corresponding relatively low-resolution image frames, of overlapping portions of a panoramic scene. A map or other information is stored relating to the generation of a low-res panorama. A main panorama image is formed by joining main image frames based on the map or other information gained in the low-res process.

Abstract: A technique of generating a panoramic image involves acquiring a set of at least two main image frames, as well as corresponding generating and/or acquiring corresponding relatively low-resolution image frames, of overlapping portions of a panoramic scene. A map or other information is stored relating to the generation of a low-res panorama. A main panorama image is formed by joining main image frames based on the map or other information gained in the low-res process.

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 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 face is detected and identified within an acquired digital image. One or more features of the face is/are extracted from the digital image, including two independent eyes or subsets of features of each of the two eyes, or lips or partial lips or one or more other mouth features and one or both eyes, or both. A model including multiple shape parameters is applied to the two independent eyes or subsets of features of each of the two eyes, and/or to the lips or partial lips or one or more other mouth features and one or both eyes. One or more similarities between the one or more features of the face and a library of reference feature sets is/are determined. A probable facial expression is identified based on the determining of the one or more similarities.

Abstract: A method of making an image in a digital camera comprises capturing a digital image of a scene into which the camera user is to be inserted, and superimposing a symbol (subject locator) onto the scene image representing at least a part of a human subject. The subject locator is scaled to a desired size and moved to a desired position relative to the scene image. Next a digital image of the user is captured, and at least the part of the user image represented by the subject locator is extracted. The part of the user image represented by the subject locator is scaled (before or after extraction) to substantially the same size as the subject locator and inserted into the first image at the position of the subject locator.

Abstract: Within a digital acquisition device, acquisition parameters of a digital image are perfected as part of an image capture process using face detection within said captured image to achieve one or more desired image acquisition parameters. Default values are determined of one or more image attributes of at least some portion of the digital image. Values of one or more camera acquisition parameters are determined. Groups of pixels are identified that correspond to an image of a face within the digitally-captured image. Corresponding image attributes to the groups of pixels are determined. One or more default image attribute values are compared with one or more captured image attribute values based upon analysis of the image of the face. Camera acquisition parameters are then adjusted corresponding to adjusting the image attribute values.

Abstract: A digital camera that automatically corrects dust artifact regions within acquired images by compiling a dust map includes an optical system for acquiring an image with a corresponding dust calibration table for such optical system, including a lens assembly and an aperture stop, in which the corresponding dust calibration map can reside. A transformation between the dust map and the specific lens calibration table, enables the use for a single dust map in multiple instances of lenses and focal length, without the need to recalibrate the digital camera for each instance.

Abstract: A digital image acquisition system includes a portable apparatus for capturing digital images and a digital processing component for detecting, analyzing, invoking subsequent image captures and informing the photographer regarding motion blur, and for reducing camera motion blur in an image captured by the apparatus. The digital processing component operates by comparing the image with at least one other image, for example a preview image, of nominally the same scene taken outside the exposure period of the main image. In one embodiment the digital processing component identifies at least one feature in a single preview image which is relatively less blurred than the corresponding feature in the main image, calculates a point spread function (PSF) in respect of such feature, and initiates a subsequent capture if determined that the motion blur exceeds a certain threshold.

Abstract: A digital image acquisition system having no photographic film comprises an apparatus for capturing digital images and a flash unit for providing illumination during image capture. The system has a portrait mode for generating an image of a foreground object against a blurred background, the portrait mode being operable to capture first, second and third images (A, B and C) of nominally the same scene. One of the first and second images (A, B) is taken with flash and the other is taken without flash, and the third image (C) is blurred compared to the first and second images. The portrait mode is further operable to determine foreground and background regions of the scene using the first and second images (A, B), and to substitute the blurred background of the third image (C) for the background of an in-focus image of the scene. In one embodiment the in-focus image is one of the first and second images. In another embodiment the in-focus image is a fourth image.

Abstract: An image acquisition device includes a first speed-optimized filter for producing a first set of candidate red-eye regions for an acquired image; and a second analysis-optimized filter for operating on the first set of candidate red eye regions and the acquired image.

Abstract: A method of determining face recognition profiles for a group persons includes determining with a multi-classifier face detector that a face region within a digital image has above a threshold probability of corresponding to a first person of the group, and recording probability scores which are analyzed for each classifier, including determining a mean and variance for each classifier for the first person. The process is repeated for one or more other persons of the group. A sub-set of classifiers is determined which best differentiates between the first person and the one or more other persons. The sub-set of classifiers is stored in association with the first person as a recognition profile.

Abstract: A face recognition technique includes using a multi-classifier face detector to determine above a threshold probability that region of an image includes a face. Further probability values are determined for a set of classifiers for the region to provide a recognition profile. Face detection and recognition probabilities are determined for at least one classifier of the set. The recognition profile is compared against a predetermined recognition profile to determine a degree of match.

Abstract: A method and system for image recognition in a collection of digital images includes training image classifiers and retrieving a sub-set of images from the collection. For each image in the collection, any regions within the image that correspond to a face are identified. For each face region and any associated peripheral region, feature vectors are determined for each of the image classifiers. The feature vectors are stored in association with data relating to the associated face region. At least one reference region including a face to be recognized is/are selected from an image. At least one classifier on which said retrieval is to be based is/are selected from the image classifiers. A respective feature vector for each selected classifier is determined for the reference region. The sub-set of images is retrieved from within the image collection in accordance with the distance between the feature vectors determined for the reference region and the feature vectors for face regions of the image collection.

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 extacted 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: An image acquisition device includes a flash and optical system for capturing digital images. A partial face tracker identifies partial face regions within a series of one or more relatively low resolution reference images, and predicts partial face regions within a main digital image. A red-eye filter for modifies an area within the main digital image indicative of a red-eye phenomenon based on an analysis of the partial face regions identified and predicted by the partial face tracker.

Abstract: An image acquisition device includes a flash and optical system for capturing digital images. A face tracker identifies face regions within a series of one or more relatively low resolution reference images, and predicts face regions within a main digital image. A face analyzer determines one or more partial face regions within the one or more face regions each including at least one eye. A red-eye filter modifies an area within the main digital image indicative of a red-eye phenomenon based on an analysis of one or more partial face regions within the one or more face regions identified and predicted by the face tracker.