Fotonation Limited

Adeia Semiconductor Bonding Technologies Inc.

George Susanu

Igor Barcovschi

Peter Corcoran

Serghei Carateev

Petronel Bigioi

Alexandru Drimbarean

Florin Nanu

Piotr Stec

Stefan Petrescu

Adrian Dorin Capata

Mihnea Gangea

Larry Murray

Dan Filip

A technique of generating a stereoscopic panorama image includes panning a portable camera device, and acquiring multiple image frames. Multiple at least partially overlapping image frames are acquired of portions of the scene. The method involves registering the image frames, including determining displacements of the imaging device between acquisitions of image frames. Multiple panorama images are generated including joining image frames of the scene according to spatial relationships and determining stereoscopic counterpart relationships between the multiple panorama images. The multiple panorama images are processed based on the stereoscopic counterpart relationships to form a stereoscopic panorama image.

Stereoscopic (3D) panorama creation on handheld device

A hand-held digital camera has a touch-sensitive display screen ('touch screen') for image preview and user control of the camera, and a user-selectable panorama mode. Upon entering panorama mode the camera superimposes upon the touch screen a horizontal rectangular bar whose width and/or height are user-adjustable by interaction with the touch screen to select a desired horizontal sweep angle. After the sweep angle is set the camera automatically captures successive horizontally overlapping images during a sweep of the device through the selected sweep angle. Subsequently the camera synthesises a panoramic image from the successively captured images, the panoramic image having a width corresponding to the selected sweep angle.

Digital image capture device having a panorama mode

A hand-held digital camera has a touch-sensitive display screen ('touch screen') for image preview and user control of the camera, and a user-selectable panorama mode. Upon entering panorama mode the camera superimposes upon the touch screen a horizontal rectangular bar whose width and/or height are user-adjustable by interaction with the touch screen to select a desired horizontal sweep angle. After the sweep angle is set the camera automatically captures successive horizontally overlapping images during a sweep of the device through the selected sweep angle. Subsequently the camera synthesizes a panoramic image from the successively captured images, the panoramic image having a width corresponding to the selected sweep angle.

Faces in images are quickly detected with minimal memory resource usage. Instead of calculating a Haar-like feature value by subtracting the average pixel intensity value in one rectangular region from the average pixel intensity value in another, adjacent rectangular region, a face-detection system calculates that Haar-like feature value by dividing the average pixel intensity value in one rectangular region by the average pixel intensity value in another adjacent rectangular region. Thus, each Haar-like value is calculated as a ratio of average pixel intensity values rather than as a difference between such average pixel intensity values. The feature values are calculated using this ratio-based technique both during the machine-learning procedure, in which the numerical ranges for features in known face-containing images are learned based on labeled training data, and during the classifier-applying procedure, in which an unlabeled image's feature values are calculated and compared to the previously machine-learned numerical ranges.

Face detection using division-generated Haar-like features for illumination invariance

Faces in images are quickly detected with minimal memory resource usage. Instead of calculating a Haar-like feature value by subtracting the average pixel intensity value in one rectangular region from the average pixel intensity value in another, adjacent rectangular region, a face-detection system calculates that Haar-like feature value by dividing the average pixel intensity value in one such rectangular region by the average pixel intensity value in the other such adjacent rectangular region. Thus, each Haar-like value is calculated as a ratio of average pixel intensity values rather than as a difference between such average pixel intensity values. The feature values are calculated using this ratio-based technique both during the machine-learning procedure, in which the numerical ranges for features in known face-containing images are learned based on labeled training data, and during the classifier-applying procedure, in which an unlabeled image's feature values are calculated and compared to the previously machine-learned numerical ranges.

Face detection using division-generated haar-like features for illumination invariance

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.

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Headford, Ireland

George Susanu