Abstract: A method of 3D motion reconstruction of outdoor, highly flexible moving subjects with multiple cameras on drones is described herein. A multi-drone capturing system is used to remove the restriction of a dedicated virtual reality shooting place, “the hot seat,” so that the actor/target is able to perform agile or long-distance activities outdoor. The subject's 3D pose parameters are estimated by the captured multi-view images by the drones, and the sequence of poses becomes the motion in time to control the animation of a pre-built 3D model. The method is able to be directly integrated into an existing Virtual Reality/Augmented reality (VR/AR) production chain, and the subject is able to be extended to animals that are difficult to be contained in a VR camera mesh space.

Abstract: A method for optimization of alignment of pixels of X different types on a sensor array for the performance of N different camera tasks, where X and N are integers greater than 1, includes obtaining an output of each of the X types of pixel on the sensor array for an input image; evaluating the quality of the output for each of the N different camera tasks; and obtaining an optimal pixel alignment pattern by adjustment of a potential pixel alignment pattern with respect to performance of the N different camera tasks subject to a user-determined balance of priorities among the N different camera tasks.

Abstract: A method of camera control for a camera capturing images of a target includes a sequence of at least four steps. The first step determines in real time a location of a drone and a pose of a camera on the drone. The second step, which may occur before or after the first step, determines in real time a location of a reference object, the location of the reference object having a fixed relationship to a location of the target. The third step uses the determined locations to calculate a distance, characterized by magnitude and direction, between the target and the drone. The fourth step uses the calculated distance to control the pose of the camera such that an image captured by the camera includes the target. Controlling the pose of the camera does not require any analysis of the captured image.

Abstract: A system of imaging a scene includes a plurality of drones, each drone moving along a corresponding flight path over the scene and having a drone camera capturing, at a corresponding first pose and first time, a corresponding first image of the scene; a fly controller that controls the flight path of each drone, in part by using estimates of the first pose of each drone camera provided by a camera controller, to create and maintain a desired pattern of drones with desired camera poses; and the camera controller, which receives, from the drones, a corresponding plurality of captured images, processing the received images to generate a 3D representation of the scene as a system output, and to provide the estimates of the first pose of each drone camera to the fly controller. The system is fully operational with as few as one human operator.

Abstract: A method of camera control for a camera capturing images of a target includes a sequence of at least four steps. The first step determines in real time a location of a drone and a pose of a camera on the drone. The second step, which may occur before or after the first step, determines in real time a location of a reference object, the location of the reference object having a fixed relationship to a location of the target. The third step uses the determined locations to calculate a distance, characterized by magnitude and direction, between the target and the drone. The fourth step uses the calculated distance to control the pose of the camera such that an image captured by the camera includes the target. Controlling the pose of the camera does not require any analysis of the captured image.

Abstract: A system and method for calibration of cameras on Unmanned Aerial Vehicles (UAVs) is provided. The system receives a set of anchor images of a human subject from a set of anchor cameras and a group of images of the human subject from multiple viewpoints in three-dimensional (3D) space from a group of cameras on a group of UAVs. The system determines a first set of two-dimensional (2D) positions of human joints from the set of anchor images and a second set of 2D positions of the human joints from the group of images. The system computes, as 3D key-points, 3D positions of the human joints based on triangulation using the first set of 2D positions and determines a 2D re-projection error between the 3D key-points and the second set of 2D positions. Thereafter, by minimizing the 2D re-projection error, the system calibrates each camera of the group of cameras.

Abstract: Herein disclosed includes the manufacture of sheets from a titanium alloy having a chemical composition efficiently balanced with manufacturability based on known conventional manufacturing techniques for finished products exhibiting low temperature superplastic forming properties. The result is achieved by a sheet material for low temperature superplastic made of titanium alloy with the following content of element by % wt.: 4.5-5.5Al, 4.5-5.5V, 0.1-1.0Mo, 0.8-1.5Fe, 0.1-0.5Cr, 0.1-0.5Ni, 0.16-0.25O, remainder is titanium and residual elements and having molybdenum structural equivalent [Mo]eqiv.>5 and aluminum structural equivalent [Al]equiv.<8; the equivalent values are calculated from the expressions: [Mo]eqiv.=[Mo]+[V]/1.5+[Cr]×1.25+[Fe]×2.5+[Ni]/0.8 [Al]eqiv.=[Al]+[O]×10+[Zr]/6.

Abstract: Various aspects of a system and a method for camera calibration by use of a rotatable three-dimensional (3-D) calibration object are disclosed herein. In accordance with an embodiment, the system includes a first electronic device, which determines a rotation pattern of the 3-D calibration object, based on a set of pre-selected images. The set of pre-selected images includes the 3-D calibration object captured at pre-defined viewing angles. Control information is communicated by the first electronic device to a second electronic device associated with the 3-D calibration object to rotate the 3-D calibration object in accordance with the determined rotation pattern. A plurality of image frames of the 3-D calibration object are captured to calibrate intrinsic and/or extrinsic camera parameters of the first electronic device.

Abstract: Various aspects of a system and method for utilization of multiple-camera network to capture static and/or motion scenes are disclosed herein. The system comprises a plurality of unmanned aerial vehicles (UAVs). Each of the plurality of UAVs is associated with an imaging device configured to capture a plurality of images. A first UAV of the plurality of UAVs comprises a first imaging device configured to capture a first set of images of one or more static and/or moving objects. The first UAV is configured to receive focal lens information, current location and current orientation from one or more imaging devices. A target location and a target orientation of each of the one or more imaging devices are determined. Control information is communicated to the one or more other UAVs to modify the current location and current orientation to the determined target location and orientation of each of the one or more imaging devices.

Abstract: Various aspects of a method and a system for image processing are disclosed herein. The method includes processing an input image, which comprises structure information and detail information, using image processing (IP) blocks in an image processing pipeline. One or more of the IP blocks, such as the “lossy” IP blocks, process the input image with at least a partial loss of the detail information. By replacing the “lossy” IP blocks with redesigned image processing (IP) modules, the image processing pipeline reduces or avoids such loss of the detail information. A more efficient implementation of the improved pipeline is realized by using a master IP module when the “lossy” IP blocks are reordered and grouped together in the image processing pipeline. The method is further extended to process 3-D images to reduce or avoid loss of detail information in a 3-D image processing pipeline.

Abstract: A light-field adaptor for an interchangeable lens camera having an adaptor housing including a first end configured to be received in a mount interface of a camera and a second end configured to be coupled to a mount interface of an interchangeable lens, and a lens array disposed within the housing. The lens array includes a plurality of lenses disposed at a plurality of distances from the camera sensor and illuminates different areas of the sensor to capture information about the light field emanating from a scene. The lens array may be sized and positioned to use a captured light field to generate one or more of infinite—depth of field rendering, shallow depth of field rendering, and images focused at different scene depths.

Abstract: Various aspects of a system and a method for extrinsic camera parameters calibration by use of a three dimensional (3D) calibration are disclosed herein. In accordance with an embodiment, the system includes an electronic device, which receives an image, which includes the 3D calibration object with a plurality of unique identifiers. One or more appearance parameters of the 3D calibration object and/or a plurality of intrinsic camera parameters of an image-capturing device that captured the received image, are further received. A positional probability is computed for each of the plurality of unique identifiers distributed in the received image. The plurality of unique identifiers of the 3D calibration object are located in the received image to calibrate the extrinsic camera parameters based on the computed positional probability, the received one or more appearance parameters of the 3D calibration object, and the plurality of intrinsic camera parameters.

Abstract: A method to position multiple camera using camera ordering is described herein. Based on two known camera positions, a third camera position is able to be determined using acquired information and calculations.

Abstract: A method to estimate a set of camera locations, in clockwise or counter-clockwise order, according to the videos captured by these cameras is described herein. In some embodiments, the cameras are assumed to be fixed, with no or very mild tilting angles and no rolling angles (the horizon is horizontal in each camera image). The difference of orientation (rolling angle) between each neighboring (closest) camera pair is able to be up to 45 degrees. Each camera is assumed to have overlapped views with at least one other camera. Each camera has one right neighboring camera and one left neighboring camera, except the first and the last cameras which have only one neighboring camera at one side. The locations of the cameras then are able to be expressed as a unique list counter-clockwise. The input videos are assumed to be synchronized in time.

Abstract: The thick lens calibration method enables better calibration of complex camera devices such as devices with thick lens systems. The thick lens calibration method includes a two step process of calibrating using the distance between a second nodal point and an image sensor, and calibrating using the distance between the first and second nodal point.

Abstract: Various aspects of a method and system to track one or more objects in a video stream are disclosed herein. In accordance with an embodiment, the method includes computation of a first confidence score of a first geometrical shape that encompasses at least a portion of an object in a first image frame of the video stream. The first geometrical shape is utilized to track the object in the video stream. The first geometrical shape is split into a plurality of second geometrical shapes. The split of the first geometrical shape is based on a comparison of the computed first confidence score with a pre-defined threshold score.

Abstract: Various aspects of a system and a method for extrinsic camera parameters calibration by use of a three dimensional (3D) calibration are disclosed herein. In accordance with an embodiment, the system includes an electronic device, which receives an image, which includes the 3D calibration object with a plurality of unique identifiers. One or more appearance parameters of the 3D calibration object and/or a plurality of intrinsic camera parameters of an image-capturing device that captured the received image, are further received. A positional probability is computed for each of the plurality of unique identifiers distributed in the received image. The plurality of unique identifiers of the 3D calibration object are located in the received image to calibrate the extrinsic camera parameters based on the computed positional probability, the received one or more appearance parameters of the 3D calibration object, and the plurality of intrinsic camera parameters.

Abstract: Various aspects of a method and system for object tracking are disclosed herein. The method comprises computation of an overlap value between a first bounding box and a second bounding box, associated with an object in an image frame of a video stream. The overlap values are utilized to track the object in the video stream. The first bounding box encompasses at least a partial first portion of an object. The second bounding box encompasses at least a partial second portion of the object. A first score associated with the first bounding box and a second score associated with the second bounding box is computed based on a comparison of the computed overlap value with a pre-defined threshold value. The first bounding box is updated to a new bounding box that at least partially encompasses the object, based on the computed first score and the computed second score.

Abstract: Various aspects of a system and a method for camera calibration by use of a rotatable three-dimensional (3-D) calibration object are disclosed herein. In accordance with an embodiment, the system includes a first electronic device, which determines a rotation pattern of the 3-D calibration object, based on a set of pre-selected images. The set of pre-selected images includes the 3-D calibration object captured at pre-defined viewing angles. Control information is communicated by the first electronic device to a second electronic device associated with the 3-D calibration object to rotate the 3-D calibration object in accordance with the determined rotation pattern. A plurality of image frames of the 3-D calibration object are captured to calibrate intrinsic and/or extrinsic camera parameters of the first electronic device.

Abstract: Various aspects of a system and method for utilization of multiple-camera network to capture static and/or motion scenes are disclosed herein. The system comprises a plurality of unmanned aerial vehicles (UAVs). Each of the plurality of UAVs is associated with an imaging device configured to capture a plurality of images. A first UAV of the plurality of UAVs comprises a first imaging device configured to capture a first set of images of one or more static and/or moving objects. The first UAV is configured to receive focal lens information, current location and current orientation from one or more imaging devices. A target location and a target orientation of each of the one or more imaging devices are determined. Control information is communicated to the one or more other UAVs to modify the current location and current orientation to the determined target location and orientation of each of the one or more imaging devices.