A method for detecting a parallax problem in sensor data from two sensors spaced apart from each other and at least partly capturing the same environment, wherein at least one of the sensors provides distance information. The method includes obtaining the acquired sensor data from the sensors; assigning measured values in the acquired sensor data of one sensor to corresponding measured values in the acquired sensor data of the other sensor, wherein the assignment takes the respective imaging conditions of the two sensors into account; consecutively numbering the measured values in the sensor data; checking whether a sorting order of the numbering of the measured values that correspond to each other matches, a parallax problem being determined in response to a sorting order not matching; and outputting a test result. Also disclosed is an apparatus for detecting a parallax problem in sensor data from two sensors and a transportation vehicle.

A method for detecting a parallax problem in sensor data from two sensors spaced apart from each other and at least partly capturing the same environment, wherein at least one of the sensors provides distance information. The method includes obtaining the acquired sensor data from the sensors; assigning measured values in the acquired sensor data of one sensor to corresponding measured values in the acquired sensor data of the other sensor, wherein the assignment takes the respective imaging conditions of the two sensors into account; consecutively numbering the measured values in the sensor data; checking whether a sorting order of the numbering of the measured values that correspond to each other matches, a parallax problem being determined in response to a sorting order not matching; and outputting a test result. Also disclosed is an apparatus for detecting a parallax problem in sensor data from two sensors and a transportation vehicle.

Methods and/or apparatus provide for obtaining intrinsics and extrinsics of a plurality of cameras arranged to capture a scene and based thereon, generate a voxel representation of the scene; obtaining extrinsics and intrinsics of a virtual camera; mapping the extrinsics and intrinsics of the virtual camera to at least one voxel surface defined in a data structure and to identify at least one camera pair suitable for obtaining depth data for that voxel surface based on the corresponding camera pair identifier; and receiving an input from the mapping unit, and in response obtaining images captured by the cameras in the at least one camera pair identified as being suitable for reconstructing the scene from the viewpoint of the virtual camera, and to generate an image of the scene from the viewpoint of the virtual camera based on the obtained images.

A three-dimensional model distribution method includes generating a depth image from a three-dimensional model; and distributing the depth image and information for restoring the three-dimensional model from the depth image.

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.

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.

A method and system for registering a 3D sensor with an autonomous manipulator is provided. The 3D sensor has a field of view and a sensor coordinate system. The autonomous manipulator is a vision-guided manipulator having a work envelope and a manipulator coordinate system. The method includes moving a registration target relative to the sensor in the field of view of the sensor in the work envelope to obtain a plurality of depth maps or images of the target. The depth maps or images are processed to obtain a plurality of extrinsic registration parameters between the manipulator and the sensor.

A method and system for registering a 3D sensor with an autonomous manipulator is provided. The 3D sensor has a field of view and a sensor coordinate system. The autonomous manipulator is a vision-guided manipulator having a work envelope and a manipulator coordinate system. The method includes moving a registration target relative to the sensor in the field of view of the sensor in the work envelope to obtain a plurality of depth maps or images of the target. The depth maps or images are processed to obtain a plurality of extrinsic registration parameters between the manipulator and the sensor.

An optical imaging system for imaging a target during a medical procedure, the optical imaging system involving a first camera for capturing a first image of the target, a second wide-field camera for capturing a second image of the target, at least one optional path folding mirror disposed in an optical path between the target and a lens of the second camera, and a processor for receiving the first image and the second image, the processor configured to apply an image transform to one of the first image and the second wide-field image and combine the transformed image with the other one of the images to produce a stereoscopic image of the target.

A method and a system for generating a multiview stereoscopic image are provided. The method includes the following steps. An image capturing apparatus captures a real calibration panel to obtain multiple images, and a processor obtains a datum image and multiple images to be calibrated by analyzing the images including the real calibration panel. The processor respectively calculates a homography matrix of each of the images to be calibrated corresponding to the datum image according to the datum image and the images to be calibrated. The processor obtains a calibration matrix of the homography matrix by performing a matrix disassembly calculation on each of the homography matrices. The processor multiplies the images to be calibrated by the corresponding calibration matrix to obtain multiple calibrated images. The processor outputs the multiview stereoscopic image including the datum image and the calibrated images.