Abstract: Procedures are described for blending images in real-time that avoid ghosting artifacts (attributable to moving objects), maintain the proper appearance of contiguous edges in the final image, and permits the use of fast (real-time) blending operations. A “guard-band” may be defined around an initially identified seam that perturbs the path of the initial seam so that both the seam and the guard-band's edges avoid moving objects by at least a specified amount. Rapid blend operations may then be performed in the region demarcated by the guard-band. The seam may be further adjusted to bias its position toward a specified trajectory within the overlap region when there is no moving object present. If visual registration techniques are not able to provide a properly aligned overlap region, motion sensor data for the image capture device, may be used instead to facilitate blending operations.

Abstract: A method for dynamically calibrating rotational offset in a device includes obtaining an image captured by a camera of the device. Orientation information of the device at the time of image capture may be associated with the image. Pixel data of the image may be analyzed to determine an image orientation angle for the image. A device orientation angle may be determined from the orientation information. A rotational offset, based on the image orientation angle and the device orientation angle, may be determined. The rotational offset is relative to the camera or orientation sensor. A rotational bias may be determined from statistical analysis of numerous rotational offsets from numerous respective images. In some embodiments, various thresholds and predetermined ranges may be used to exclude some rotational offsets from the statistical analysis or to discontinue processing for that image.

Abstract: Systems, methods, and computer readable media to register images in real-time and that are capable of producing reliable registrations even when the number of high frequency image features is small. The disclosed techniques may also provide a quantitative measure of a registration's quality. The latter may be used to inform the user and/or to automatically determine when visual registration techniques may be less accurate than motion sensor-based approaches. When such a case is detected, an image capture device may be automatically switched from visual-based to sensor-based registration. Disclosed techniques quickly determine indicators of an image's overall composition (row and column projections) which may be used to determine the translation of a first image, relative to a second image. The translation so determined may be used to align/register the two images.

Abstract: Procedures are described for blending images in real-time that avoid ghosting artifacts (attributable to moving objects), maintain the proper appearance of contiguous edges in the final image, and permits the use of fast (real-time) blending operations. A “guard-band” may be defined around an initially identified seam that perturbs the path of the initial seam so that both the seam and the guard-band's edges avoid moving objects by at least a specified amount. Rapid blend operations may then be performed in the region demarcated by the guard-band. The seam may be further adjusted to bias its position toward a specified trajectory within the overlap region when there is no moving object present. If visual registration techniques are not able to provide a properly aligned overlap region, motion sensor data for the image capture device, may be used instead to facilitate blending operations.

Abstract: Systems, methods, and computer readable media for stitching or aligning multiple images (or portions of images) to generate a panoramic image are described. In general, techniques are disclosed for using motion data (captured at substantially the same time as image data) to align images rather than performing image analysis and/or registration operations. More particularly, motion data may be used to identify the rotational change between successive images. The identified rotational change, in turn, may be used to calculate a motion vector that describes the change in position between a point in a first image and a corresponding point in a subsequent image. The motion vector may be utilized to align successive images in an image sequence based on the motion data associated with the images.