A system for manufacturing a 3D protective film includes a raw material processing device configured to process an intermediate raw material, which is a raw material of an intermediate liquid crystal protection film included in the protective film for protecting a liquid crystal surface of the electronic device, an upper raw material, which is a raw material of a hard coating surface protection film formed on an upper portion of the intermediate liquid crystal protection film, and a lower raw material which is a raw material of an adhesive surface protection film formed on a lower portion of the intermediate liquid crystal protection film, a laminating device configured to form a raw lamination material by laminating the upper raw material, the lower raw material, and the intermediate raw material, and a shape processing device configured to form the pre-formed protective film by processing the raw lamination material.

A method for correcting a camera by using a plurality of pattern members placed on the ground of a vehicle enables receiving pattern information of a plurality of pattern members by using a plurality of cameras disposed on the circumference of a vehicle being driven, calculating a first parameter on the basis of the pattern information, calculating trajectory information of the vehicle by using the pattern information, and calculating a second parameter by correcting the first parameter on the basis of the trajectory information of the vehicle.

A method of generating a three-dimensional model of an object, is executed by a processor. The method includes executing rendering of the three-dimensional model of the object based on an image captured by the imaging device; and modifying the three-dimensional model.

In a system and method of calibrating a stereoscopic camera, a target pattern is electronically displayed on a display. The camera to be calibrated captures images of the target pattern using a stereoscopic camera while the displayed target pattern is altered over time. The captured images are analyzed and calibration parameters for the stereoscopic camera are determined.

An object tracking system that includes a sensor that is configured to capture frames of at least a portion of a global plane for a space. The system is configured to receive a first frame from the sensor and to identify a first pixel location and a second pixel location within the first frame. The system is further configured to determine (x,y) coordinates by applying a homography to the first pixel location and the second pixel location. The system is further configured to determine an estimated distance between the (x,y) coordinates, to determine an actual distance, and to determine a distance difference between the estimated distance and the actual distance. The system is further configured to compare the distance difference to a difference threshold level and to recompute the homography in response to determining that the distance difference exceeds the difference threshold level.

Systems and methods for generating augmented reality environments from 2D drawings are provided. The system performs a camera calibration process to determine how a camera transforms images from the real world into a 2D image plane. The system calculates a camera pose and determines an object position and an object orientation relative to a known coordinate system. The system detects and processes a 2D drawing/illustration and generates a 3D model from the 2D drawing/illustration. The system performs a rendering process, wherein the system generates an augmented reality environment which includes the 3D model superimposed on an image of the 2D drawing/illustration. The system can generate the augmented reality environment in real time, allowing the system to provide immediate feedback to the user. The images processed by the system can be from a video, from multiple image photography, etc.

A camera is located at a position deviated from directly above a center of a placement location of a workpiece. When a photographed image is generated by photographing, with the camera, the placement location at which the workpiece is placed, an image processing device specifies, by using a preliminarily determined conversion parameter, to which pixels in the photographed image two-dimensional coordinates within a photographed three-dimensional space correspond, aligns the specified pixels corresponding to the respective coordinates in a two-dimensional manner, and generates a corrected photographed image in which a trapezoidal distortion in the photographed image is corrected. A robot control device detects a position of the workpiece at the placement location based on the corrected photographed image, and controls a workpiece retention robot so as to retain the workpiece and transport the workpiece to a processing machine.

Computer-implemented image correction for a biomarker test includes a biomarker test which has a calibration array and a biomarker site, wherein the calibration array comprises plural colored patches and the biomarker site is color-responsive to indicate a measurement of biomarkers present. The method comprises: storing a reference color value for each of the plural colored patches; receiving an image of the biomarker test; defining shading of pixels of the image as D, a combination of a plurality of basis functions; defining a color correction matrix, M having parameters that when solved correct color of the calibration array in the image to the corresponding stored values; solving D and M for pixels of the image excluding pixels of the biomarker site; using D and M to interpolate values for pixels of the biomarker site of the image to generate a color and shading corrected image of the biomarker site.

An orientation-position determining device is provided which is used for a sensor installed in a vehicle. The orientation-position determining device includes an imaging unit and an orientation-position detector. The imaging unit works to obtain a ranging image and an ambient light image from the sensor. The ranging image represents a distance to a target lying in a light emission region to which light is emitted from the sensor. The ambient light image represents an intensity of ambient light and has a resolution higher than that of the ranging image. The orientation-position detector works to use the ranging image and the ambient light image to detect an orientation and/or a position of the sensor.

A processor-implemented method with sensor calibration includes: estimating a portion of a rotation parameter for a target sensor among a plurality of sensors based on a capture of a reference object; estimating another portion of the rotation parameter for the target sensor based on an intrinsic parameter of the target sensor and a focus of expansion (FOE) determined based on sensing data collected with consecutive frames by the target sensor while the electronic device rectilinearly moves based on one axis; and performing calibration by determining a first extrinsic parameter for the target sensor based on the portion and the other portion of the rotation parameter.