A method is provided for the transformation of a moving image sequence and a moving image sequence transformation device designed for executing the transformation method. For a current individual image of the moving image sequence, the method forms a transformation basis (1) in which a first individual image, the current individual image, and a second individual image are arranged adjacent to each other. Intersection points (S1, S2) are determined for connecting lines (7, 8) which extend from image points corresponding to each other from the first individual image and the current individual image and from the current individual image to the second individual image, comprising image starting limits and image end limits (15, 16) of the current individual image. A new image point position of an image point in the current individual image results from averaging the intersection points.

Methods and systems for coded rolling shutter are provided. In accordance with some embodiments, methods and system are provided that control the readout timing and exposure length for each row of a pixel array in an image sensor, thereby flexibly sampling the three-dimensional space-time value of a scene and capturing sub-images that effectively encode motion and dynamic range information within a single captured image.

Provided is an interchangeable lens digital camera that is capable of correcting a rolling shutter distortion in a live view image without delay in displaying the image. At the start of live view imaging, a lens controller in an interchangeable lens controls a shake detection sensor to detect the direction and amount of a shake, and produces deviation information on the basis of shake detection signals from the shake detection sensor, the deviation information indicating fluctuation in direction and amount of the shake for one frame of the live view image in the form of a parameter. The deviation information is transmitted to a body controller of a camera body through a serial communication unit, to correct the rolling shutter distortion on the basis of the deviation information.

An error estimation device includes an error prediction unit and a determination unit. The error prediction unit is configured to predict a bias error occurring in an inertial sensor mounted in a vehicle. The determination unit is configured to determine whether the bias error needs to be repredicted by the error prediction unit based on a reflection distance image acquired by an optical sensor in a rolling shutter mode and an outside light image acquired by an external camera in a global shutter mode.

An electronic device is provided. The electronic device includes a housing, a camera module, a memory, a gyro sensor, and a processor. The housing may include a front plate, a rear plate, and a lateral member surrounding a space between the front plate and the rear plate. The camera module may include a first camera disposed in the space and performing shooting based on a first direction, a second camera disposed in the space and performing shooting based on a second direction, and an image signal processor for correcting images. The processor may be configured to control at least one of the first camera or the second camera to capture images, to identify a camera switching command while capturing the images, to acquire gyro motion information through the gyro sensor in response to the camera switching command, and to control the image signal processor to correct the captured images.

Posture information corresponding to a line of an input image is calculated. Then, a first virtual line, which is a line in a line direction of the input image for which the posture information calculated is common, is rotated according to the posture information to obtain a second virtual line on the output image. For each pixel of the output image, a corresponding second virtual line is calculated, and posture information is obtained on the basis of the corresponding second virtual line. Then, for coordinates of each pixel of the output image, the reference coordinates on the input image corresponding to the pixel coordinates is calculated using the associated posture information. By cutting out the output image from the input image on the basis of the reference pixel, highly accurate distortion correction can be realized even in a case where the camera posture differs depending on the line.

A blur correction device includes: an acquisition unit that acquires an amount of blur correction used to correct blurring of an image obtained through imaging of an imaging element during exposure for one frame in the imaging element; and a correction unit that corrects the blurring by performing image processing on a correction target image, which is an image for one frame included in a moving image obtained through imaging of the imaging element, based on the amount of blur correction acquired by the acquisition unit during exposure necessary to obtain the correction target image.

A method and/or system is disclosed for creating panoramic images from a group of networked devices. Optionally, the system will identify available recording devices located around an event. In some embodiments, the system will arrange for some level of control and/or access to the devices. For example, there may be a large number of people carrying cell phones in and around the event. Optionally, the system collects pictures from the different devices and make a collage recording of the event. For example, the system may recognize an event and/or be informed of an event. In some embodiments, the system will make a model (e.g. a 3D and/or 4D model) and/or supply the model in a way that allows a viewer to choose views and/or times and/or “walk through” the scene.

An optical communication-based image processing system is disclosed. The system may include a transmitter having at least one light emitting element and a receiver having a rolling shutter camera. As the system is provided, a rolling shutter effect may be improved.

A system calibrates one or more sensors mounted to an autonomous vehicle. From the one or more sensors, the system identifies a primary sensor and a secondary sensor. The system determines a reference angle for the primary sensor, and based on that reference angle for the primary sensor, a scan-start time representing a start of a scan and a scan-end time representing an end of a scan. The system receives, from the primary sensor, a primary set of scan data recorded from the scan-start time to the scan-end time. The system receives, from the secondary sensor, a secondary set of sensor data recorded from the scan-start time to the scan-end time. The system calibrates the primary and secondary sensors by determining a relative transform for transforming points between the first set of scan data and the second set of scan data.