Abstract: A method of tracking faces in an image stream with a digital image acquisition device includes receiving images from an image stream including faces, calculating corresponding integral images, and applying different subsets of face detection rectangles to the integral images to provide sets of candidate regions. The different subsets include candidate face regions of different sizes and/or locations within the images. The different candidate face regions from different images of the image stream are each tracked.

Abstract: A method of processing an image comprises: acquiring an image of a scene including an object having a recognisable feature. A lens actuator setting providing a maximum sharpness for a region of the image including the object and a lens displacement corresponding to the lens actuator setting are determined. A distance to the object based on the lens displacement is calculated. A dimension of the feature as a function of the distance to the object, the imaged object size and a focal length of a lens assembly with which the image was acquired, is determined. The determined dimension of the feature is employed instead of an assumed dimension of the feature for subsequent processing of images of the scene including the object.

Abstract: An auto focus camera module includes a camera module housing defining an aperture and an internal cavity to accommodate camera module components, an image sensor coupled to or within the housing, a lens barrel within the housing that contains an optical train including at least one movable lens disposed relative to the aperture and image sensor to focus images of scenes onto the image sensor along an optical path, and a fast focus MEMS actuator coupled to one or more lenses of the optical train including the at least one movable lens and configured to rapidly move said at least one movable lens relative to the image sensor to provide autofocus for the camera module in each frame of a preview or video sequence or both.

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 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: An optical system for an image acquisition device comprises a filter comprising a central aperture arranged to transmit both visible and selected near infra-red (NIR) wavelengths and a peripheral aperture arranged to block visible wavelengths and to transmit the NIR wavelengths. An image sensor comprises an array of pixels including pixels sensitive to visible wavelengths and corresponding pixels sensitive to the NIR wavelengths. A lens assembly is axially located between the filter and the image sensor and comprises a plurality of lens elements. The lens elements are arranged to simultaneously focus NIR light received from a given object through central and peripheral apertures of the filter and visible light received from the object through the central aperture onto the sensor surface.

Abstract: A method for providing improved foreground/background separation in a digital image of a scene is disclosed. The method comprises providing a first map comprising one or more regions provisionally defined as one of foreground or background within the digital image; and providing a subject profile corresponding to a region of interest of the digital image. The provisionally defined regions are compared with the subject profile to determine if any of the regions intersect with the profile region. The definition of one or more of the regions in the map is changed based on the comparison.

Abstract: A method of generating one or more new digital images using an original digitally-acquired image including a selected image feature includes identifying within a digital image acquisition device one or more groups of pixels that correspond to the selected image feature based on information from one or more preview images. A portion of the original includes automatically generating values of pixels of one or more new images based on the selected portion in a manner which includes the selected image feature within the one or more new images.

Abstract: An optical system for an image acquisition device comprises a filter comprising a central aperture arranged to transmit both visible and selected near infra-red (NIR) wavelengths and a peripheral aperture arranged to block visible wavelengths and to transmit the NIR wavelengths. An image sensor comprises an array of pixels including pixels sensitive to visible wavelengths and corresponding pixels sensitive to the NIR wavelengths. A lens assembly is axially located between the filter and the image sensor and comprises a plurality of lens elements. The lens elements are arranged to simultaneously focus NIR light received from a given object through central and peripheral apertures of the filter and visible light received from the object through the central aperture onto the sensor surface.

Abstract: A method of estimating motion between a pair of image frames of a given scene comprises calculating respective integral images for each of the image frames and selecting at least one corresponding region of interest within each frame. For each region of interest, an integral image profile from each integral image is calculated, each profile comprising an array of elements, each element comprising a sum of pixel intensities from successive swaths of the region of interest for the frame. Integral image profiles are correlated to determine a relative displacement of the region of interest between the pair of frames. Each region of interest is divided into a plurality of further regions of interest before repeating until a required hierarchy of estimated motion for successively divided regions of interest is provided.

Abstract: A rearview imaging system for a vehicle includes at least one video camera mounted at the rear of the vehicle for providing a wide angle horizontal field of view (FoV) rearwardly of the vehicle, and a display device in the vehicle at a position viewable by the driver. A video processor subdivides the camera FoV into three horizontally disposed sub-FOVs and displaying said sub-FoVs on visually separated side-by-side regions of the display device screen. The horizontal position and/or extent of at least one sub-FoV is variable as a function of the motion of the vehicle.

Abstract: A method of image processing within an image acquisition device comprises: acquiring an image including one or more face regions and identifying one or more eye-iris regions within the one or more face regions. The one or more eye-iris regions are analyzed to identify any eye-iris region comprising an eye-iris pattern of sufficient quality to pose a risk of biometrically identifying a person within the image. Responsive to identifying any such eye-iris region, a respective substitute eye-iris region comprising an eye-iris pattern sufficiently distinct from the identified eye-iris pattern to avoid identifying the person within the image is determined, and the identified eye-iris region is replaced with the substitute eye-iris region in the original image.

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: 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 hand-held digital image capture device (digital camera) has a user-selectable mode in which upon engaging the mode the device detects a face in the field of view of the device and generates a face delimiter on a camera display screen, the delimiter surrounding the initial position of the image of a the face on the screen. The device is arranged to indicate thereafter to the user if the device departs from the movement along a predetermined concave path P with the optical axis of the device pointing towards the face, such indication being made by movement of the image of the face relative to the delimiter. The camera captures and stores a plurality of images at successive positions along the concave path.

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 handheld imaging device is described to provide high quality RAW image data to a smartphone, or similar handheld imaging device. The imaging device can have a larger dimension, particularly with regard to the thickness of the device, thus overcoming some of the physical limitations to providing high quality optics and image sensing within the thin form factor of a modern smartphone. As the device is only connected when capturing images the smartphone form factor is not altered. The device does not replicate the high-end image processing functionality of a smartphone, but instead transfers RAW images to the smartphone for high-end image processing & enhancement on the smartphone CPU/GPU. Thus it can be manufactured at lower cost than a dedicated camera with equivalent capabilities by taking advantage of the sophisticated image processing capabilities of today's smartphones.

Abstract: An estimated total camera motion between temporally proximate image frames is computed. A desired component of the estimated total camera motion is determined including distinguishing an undesired component of the estimated total camera motion, and including characterizing vector values of motion between the image frames. A counter is incremented for each pixel group having a summed luminance that is greater than a threshold. A counter may be decremented for pixels that are under a second threshold, or a zero bit may be applied to pixels below a single threshold. The threshold or thresholds is/are determined based on a dynamic luminance range of the sequence. The desired camera motion is computed including representing the vector values based on final values of counts for the image frames. A corrected image sequence is generated including the desired component of the estimated total camera motion, and excluding the undesired component.

Abstract: A method of image processing within an image acquisition device comprises: acquiring an image including one or more face regions and identifying one or more eye-iris regions within the one or more face regions. The one or more eye-iris regions are analyzed to identify any eye-iris region comprising an eye-iris pattern of sufficient quality to pose a risk of biometrically identifying a person within the image. Responsive to identifying any such eye-iris region, a respective substitute eye-iris region comprising an eye-iris pattern sufficiently distinct from the identified eye-iris pattern to avoid identifying the person within the image is determined, and the identified eye-iris region is replaced with the substitute eye-iris region in the original 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.