Abstract: A method includes controlling an integrated camera of a mobile device to detect a plurality of fiducial markers displayed as part of a test pattern on a display surface of a color display device, wherein the test pattern is one of a plurality of test patterns, estimating a position of the integrated camera relative to the display surface, using the plurality of fiducial markers, augmenting a live image of the test pattern on a display of the mobile device with an overlay, controlling, in response to a position of the overlay being aligned on the display of the mobile device with the live image of the test pattern, the integrated camera to capture an image of the test pattern, and calculating an adjustment to a color setting of the color display device, wherein the adjustment is calculated using information extracted from the image.

Abstract: This method for retrieving at least one optical parameter of an ophthalmic lens comprises: obtaining an image of a first and second patterns by using an image capture device located at a first position; from that image, obtaining a first set of data from at least a part of the first pattern that is seen through the lens by the image capture device and obtaining a second set of data from at least a part of the second pattern that is seen directly i.e. outside the lens by the image capture device; retrieving the at least one optical parameter by using the first and second sets of data and taking account of relative positions of the image capture device, the lens and the first and second patterns.

Abstract: A method for recalibrating an augmented reality (AR) device includes generating and storing a ground truth map of a real-world environment when the AR device is operating with a high likelihood of having an accurate factory calibration. During operation of the AR device, new map data is generated for the real-world environment. The new map data is compared to the ground truth map to detect potential calibration errors. If calibration errors are detected, a recalibration procedure is executed by determining an optimal path through the real-world environment that allows for observing parameters requiring recalibration. Visual cues are generated to guide a user of the AR device through the optimal path. As the user follows the visual cues, calibration parameters are iteratively adjusted to eliminate detected calibration errors. The recalibration procedure may be presented as an interactive game to improve user engagement, with rewards provided for accurately following guidance.

Abstract: This application provides a coordinate system calibration method, an automatic assembly method, and an apparatus. In the coordinate system calibration method, measured values of a measured parameter of a target object are separately measured at two different calibration heights, and then a target calibration height that matches an actual value of the measured parameter is obtained based on the two different calibration heights and the corresponding measured values of the measured parameter. This solution is not only applicable to a planar object but also applicable to a curved object.

Abstract: A system to calibrate a camera of a mobile device includes a fixture configured to hold the mobile device with the camera and a display of the mobile device exposed to an outside of the fixture; and a moving mechanism to move the fixture.

Abstract: There is proposed a new and improved information processing apparatus, an information processing method, and a program capable of more simply detecting whether or not a deviation related to a camera parameter has occurred in a plurality of cameras.

Abstract: A method for calibrating a vehicle to infrastructure system using an infrared camera overlooking a road, comprises: obtaining from the camera a first image, each image of the camera having points identifiable in an image coordinate system and corresponding to objects in a real world scene; identifying in the first image a plurality of points each of which corresponds to a respective object that is touching the road's surface; obtaining a measurement that corresponds to a distance from a location of the camera to each respective one of the points in a camera coordinate system (CCS); determining a model of the road in the CCS based on the points and their obtained distances; and calculating a transformation between the CCS and a world coordinate system (WCS) using the road model, the transformation being usable to determine a distance in the WCS to an object in a second image.

Abstract: Aspects of the present disclosure include obtaining images from a time-of-flight (TOF) sensor for determining dimensions of an object. A prompt to capture at least one image of an object can be displayed on an interface. At least one image of the object can be captured based on an interaction with the prompt. It can be determined whether multiple images including the at least one image are sufficient for performing object dimensioning, and if so, the images can be provided for performing object dimensioning to compute or display dimensions of the object.

Abstract: The present disclosure provides image generation systems and methods. The image generation method includes capturing a first 2D image corresponding to a first perspective of a 3D object, and associating the first 2D image with a set of 3D scanning data, the set of 3D scanning data comprising 3D data points corresponding to the first perspective of the 3D object. The method includes obtaining new 3D data points to include in the set of 3D scanning data from a subsequent perspective of the 3D object, the new 3D data points being non-overlapping with 3D data points already in the set of 3D scanning data. The method further includes, responsive to determining that a number of the new 3D data points exceeds a predetermined threshold, automatically capturing a subsequent 2D image corresponding to the subsequent perspective, and associating the subsequent 2D image with the new 3D data points.

Abstract: Disclosed is a method and an apparatus for processing dual-stream images. The method includes processing a wide field-of-view (FOV) image stream using a first processing technique. The method further includes storing one or more of color information, gamma or tone mapping information, semantic information from the wide FOV image stream. The method further includes processing a narrow FOV image stream using a neural network based on the one or more of the white balance information, the gamma or tone mapping information, and semantic information. The method further includes blending the processed wide FOV image stream and the processed narrow FOV image stream to generate a final image, for display on a display device.

Abstract: Provided are methods for active alignment of an optical assembly with intrinsic calibration. Some methods described include performing a first active alignment using a multi-collimator assembly, determining a principal point of the camera assembly using a diffractive optical element (DOE) intrinsic calibration module, and adjusting the relative position of one or more of the lens and the image sensor to align the principal point of the camera assembly with an image center of the image sensor and to perform a second active alignment. Systems and computer program products are also provided.

Abstract: An image capture device includes a casing, a camera module, a rotatable member, and a pan-tilt module. The casing includes front and rear casings. The camera module is disposed in the casing. A portion of the camera module is through an opening region of the front casing. The camera module includes a lens module bracket and a lens module disposed therein. The rotatable member is fixed on the lens module bracket. The rotatable member is configured to rotate the camera module when the rotatable member is rotated relative to the casing, so that the lens module is switched between horizontal and vertical shooting modes. The pan-tilt module includes a motor bracket, first and second motors. The first motor is connected between one end of the motor bracket and a sidewall of the casing. The second motor is connected to another end of the motor bracket.

Abstract: An image processing method includes: converting a red yellow blue RYB image into a grid image based on a red green blue RGB format; generating a first brightness layer of the grid image, and determining a reference gain compensation array used to adjust the first brightness layer; obtaining, based on a preset compensation array correspondence, a target gain compensation array that is associated with the reference gain compensation array and based on an RYB format; and adjusting a second brightness layer of the RYB image by using the target gain compensation array, to generate a corrected image.

Abstract: An illustrative volumetric content production system may access first capture data and second capture data. These first capture data may represent an entirety of a capture target and may be captured by a fixed camera system including a first plurality of image capture devices having respective fixed viewpoints with respect to the capture target. The second capture data may represent a portion of the capture target less than the entirety of the capture target and may be captured by a dynamic camera system including a second plurality of image capture devices having respective dynamic viewpoints with respect to the capture target. Based on the first and second capture data, the volumetric content production system may generate a volumetric representation of an object included in the portion of the capture target in accordance with principles described herein. Corresponding methods and systems are also disclosed.

Abstract: Approaches are described for image signal processor day-night detection. An exemplary approach for a camera with an infrared light source involves determining a brightness value for image data based on an average luma value for the image data, determining white balance data for the first image data, and determining, based on the white balance data for the image data and white balance data for the infrared light source, a deviation value for the image data. A transition from night mode to day mode can be effected based on comparing the brightness value for the image data to a first threshold, and comparing the deviation value for the image data to a second threshold.

Abstract: A method of installing a camera unit including an imaging device and an optical system that forms an optical image on a light receiving surface of the imaging device, wherein the light receiving surface includes a first area and a second area on a peripheral side of the first area, wherein an increase in an image height with respect to a unit half angle of view in the first area is larger than an increase in an image height with respect to a unit half angle of view in the second area, wherein the optical system and the imaging device are disposed such that the gravity center of the first area deviates in a first direction from the center of the light receiving surface, and wherein the method includes installing the camera unit such that the first direction is directed to an area other than a predetermined targeted area.

Abstract: Techniques for facilitating imager verification systems and methods are provided. In one example, an imaging device includes a focal plane array. The focal plane array includes a detector array including a plurality of detectors, where each of the plurality of detectors is configured to detect electromagnetic radiation to obtain image data. The focal plane array further includes a readout circuit configured to perform a readout to obtain the image data from each of the plurality of detectors. The imaging device further includes a processing circuit configured to perform a verification of the imaging device based at least on the image data. Related methods and systems are also provided.

Abstract: Examples disclosed herein involve a computing system configured to (i) obtain first image data captured by a first camera of a vehicle during a given period of operation of the vehicle, (ii) obtain second image data captured by a second camera of the vehicle during the given period of operation, (iii) based on the obtained first and second image data, determine (a) a candidate extrinsics transformation between the first camera and the second camera and (b) a candidate time offset between the first camera and the second camera, and (iv) based on (a) the candidate extrinsics transformation and (b) the candidate time offset, apply optimization to determine a combination of (a) an extrinsics transformation and (b) a time offset that minimizes a reprojection error in the first image data, where the reprojection error is defined based on a representation of at least one landmark that is included in both the first and second image data.

Abstract: Data processing systems are disclosed for determining semantic and person keypoints for an environment and an image and matching the keypoints for the image to the keypoints for the environment. A homography is generated based on the keypoint matching and decomposed into a matrix. Camera parameters are then determined from the matrix. A plurality of random camera poses can be generated and used to project keypoints for an environment using image keypoints. The projected keypoints can be compared to the actual keypoints for the environment to determine an error and weighting for each of the random camera poses.

Abstract: Aspects of the present invention relate to a composite image generation system (1) for a vehicle. The system includes one or more controller (10). The composite image generation system (1) has an input configured to receive first image data (DIMG1) from a first imaging device (C1), the first image data (DIMG1) has a first time stamp (TST1-(t)) indicative of a time at which the first image data (DIMG1) was captured by the first imaging device (C1); and second image data (DIMG2) from a second imaging device (C2), the second image data (DIMG2) has a second time stamp (TST2-(t)) indicative of a time at which the second image data (DIMG2) was captured by the second imaging device (C2). The one or more controller (10)is configured to compare the first time stamp (TST1-(t)) with the second time stamp (TST2-(t)) to determine a time stamp discrepancy (TST?).

Abstract: Automated techniques provide for recalibrating cameras in a real space in which puts and takes of items are tracked. The method includes first processing one or more selected images selected from a plurality of sequences of images received from a plurality of cameras calibrated using a set of calibration images that were used to calibrate the cameras previously. The first processing includes a process step to match one or more features from the selected images with features extracted from the set of calibration images using a trained neural network classifier. The features correspond to points located at displays or structures that remain substantially immobile. Camera calibrations can be updated when transform information between features matched meets or exceeds a threshold.

Abstract: Calibrating a camera and/or a lidar sensor of a vehicle or a robot involves a camera capturing images of a vehicle or robot environment. The lidar sensor emits a real pattern into the vehicle or robot environment in at least one portion of a detection range of the camera, and the real pattern is captured by the camera. A virtual pattern generated in a coordinate system of the lidar sensor is projected onto a virtual plane in the vehicle or robot environment by the lidar sensor. Laser radiation emitted by the lidar sensor penetrates the virtual plane and the real pattern correlating with the virtual pattern is generated on a real projection surface. The real pattern captured by the camera is recalculated onto the virtual plane based on a surface profile of the real projection surface. A rectified virtual pattern is generated in a coordinate system of the camera and the camera and/or lidar sensor is/are calibrated by comparing the virtual pattern and the rectified virtual pattern.

Abstract: A method for adjusting camera intrinsic parameters of a multi-camera visual tracking device is described. In one aspect, a method for calibrating the multi-camera visual tracking system includes disabling a first camera of the multi-camera visual tracking system while a second camera of the multi-camera visual tracking system is enabled, detecting a first set of features in a first image generated by the first camera after detecting that the temperature of the first camera is within the threshold of the factory calibration temperature of the first camera, and accessing and correcting intrinsic parameters of the second camera based on the projection of the first set of features in the second image and a second set of features in the second image.

Abstract: Devices, systems, and methods are provided for testing and validation of a cleaning system for a sensor such as a camera. A device may capture a first image of a target using the sensor, wherein the sensor is in a clean state, and wherein the target is in a line of sight of the sensor. The device may apply an obstruction to a portion of a lens of the sensor. The device may apply a cleaning system to the lens. The device may capture a post-clean image after applying the cleaning system. The device may determine a post-clean image quality score based on comparing the post clean image to the first image. The device may compare the post-clean image quality score to a validation threshold. The device may determine a validation state of the cleaning system based on the comparison.

Abstract: Multiview calibration is essential for accurate three-dimensional computation. However, multiview calibration can not be accurate enough because of the tolerances required in some of the intrinsic and extrinsic parameters that are associated with the calibration process, along with fundamental imperfections that are associated with the manufacturing and assembly process itself. As a result, residual error in calibration is left over, with no known methods to mitigate such errors. Residual error mitigation is presented in this work to address the shortcomings that are associated with calibration of multiview camera systems. Residual error mitigation may be performed inline with a given calibration approach, or may be presented as a secondary processing step that is more application specific. Residual error mitigation aims at modifying the original parameters that have been estimated during an initial calibration process.

Abstract: Systems and methods for calibrating an array camera are disclosed. Systems and methods for calibrating an array camera in accordance with embodiments of this invention include the capturing of an image of a test pattern with the array camera such that each imaging component in the array camera captures an image of the test pattern. The image of the test pattern captured by a reference imaging component is then used to derive calibration information for the reference component. A corrected image of the test pattern for the reference component is then generated from the calibration information and the image of the test pattern captured by the reference imaging component. The corrected image is then used with the images captured by each of the associate imaging components associated with the reference component to generate calibration information for the associate imaging components.

Abstract: An active alignment machine includes a base, a first pillar, a second pillar, a distribution module, a first alignment module, a second alignment module and a third alignment module. The first pillar has a first pillar top surface. The second pillar has a second pillar top surface. The first pillar top surface and the second pillar top surface cooperatively support plural assembling specifications. The distribution module is installed on the base and arranged between the first pillar and the second pillar. The first alignment module, the second alignment module and third alignment module are replaceable to be assembled with or dissembled from the first pillar top surface and the second pillar top surface. The first alignment module, the second alignment module and third alignment module work with the distribution module to perform the active alignment on a first-type product, a second-type product and a third-type product, respectively.

Abstract: A laundry appliance includes a basket rotatably mounted within a cabinet and defining a chamber configured for receiving a load of clothes, a water supply valve for regulating a flow of water into the chamber, and a camera assembly mounted within the cabinet in view of the chamber. A controller is configured to determine that the water supply valve is open to permit the flow of water into the chamber, identify an anticipated fog condition within the chamber based at least in part on the water supply valve being open, obtaining one or more images of the chamber using the camera assembly, analyzing the one or more images of the chamber to determine an actual fog condition in the chamber, and implementing a responsive action if the actual fog condition is different than the anticipated fog condition, e.g., providing a user notification.

Abstract: A depth measurement assembly (DMA) includes a pulsed illuminator assembly, a depth camera assembly, and a controller. The pulsed illuminator assembly has a structured light projector that projects pulses of structured light at a pulse rate into a local area. The depth camera assembly captures images data of an object in the local area illuminated with the pulses of structured light. An exposure interval of the depth camera assembly is pulsed and synchronized to the pulses projected by the pulsed illuminator assembly. The controller controls the pulsed illuminator assembly and the depth camera assembly so that they are synchronized. The controller also determine depth and/or tracking information of the object based on the captured image data. In some embodiments, the pulsed illuminator assembly have a plurality of structured light projectors that projects pulses of structured light at different times.

Abstract: Devices, systems, and methods are provided for testing and validation of a camera. A device may capture a first image of a target using a camera, wherein the camera is in a clean state, and wherein the target is in a line of sight of the camera. The device may apply an obstruction to a portion of a lens of the camera. The device may apply a camera cleaning system to the lens of the camera. The device may capture a post-clean image after applying the camera cleaning system. The device may determine a post-clean SSIM score based on comparing the post clean image to the first image. The device may compare the post-clean SSIM score to a validation threshold. The device may determine a validation state of the camera cleaning system based on the comparison.

Abstract: Technique for performing camera calibration on a vehicle is disclosed. A method of performing camera calibration includes emitting, by a laser emitter located on a vehicle and pointed towards a road, a first laser pulse group towards a first location on a road and a second laser pulse group towards a second location on the road, where each laser pulse group includes one or more laser spots. For each laser pulse group: a first set of distances are calculated from a location of a laser receiver to the one or more laser spots, and a second set of distances are determined from an image obtained from a camera, where the second set of distances are from a location of the camera to the one or more laser spots. The method also includes determining two camera calibration parameters of the camera by solving two equations.

Abstract: There is provided a system and method of re-projecting and combining sensor data of a scene from a plurality of sensors for visualization. The method including: receiving the sensor data from the plurality of sensors; re-projecting the sensor data from each of the sensors into a new viewpoint; localizing each of the re-projected sensor data; combining the localized re-projected sensor data into a combined image; and outputting the combined image. In a particular case, the receiving and re-projecting can be performed locally at each of the sensors.

Abstract: Crosstalk mitigation among cameras in neighboring monitored workcells is achieved by computationally defining a noninterference scheme that respects the independent monitoring and operation of each workcell. The scheme may involve communication between adjacent cells to adjudicate non-interfering camera operation or system-wide mapping of interference risks and mitigation thereof. Mitigation strategies can involve time-division and/or frequency-division multiplexing.

Abstract: The present disclosure relates to methods and systems that facilitate determination of a pose of a vehicle based on various combinations of map data and sensor data received from light detection and ranging (LIDAR) devices and/or camera devices. An example method includes receiving point cloud data from a (LIDAR) device and transforming the point cloud data to provide a top-down image. The method also includes comparing the top-down image to a reference image and determining, based on the comparison, a yaw error. An alternative method includes receiving camera image data from a camera and transforming the camera image data to provide a top-down image. The method also includes comparing the top-down image to a reference image and determining, based on the comparison, a yaw error.

Abstract: To obtain imaging device capable of reporting more reliably an occurrence of trouble. The imaging device of the present disclosure includes an imaging sensor configured to generate image data, a diagnosis circuit configured to perform diagnosis processing for the imaging sensor and an output circuit configured to output a flag signal corresponding to a result of the diagnosis processing, wherein the flag signal is set to a ground level signal in response to the result of the diagnosis processing indicating an error.

Abstract: In one embodiment, a wearable apparatus is provided which may include a holographic film disposed on the wearable apparatus, an eye tracking device including an image sensor and an illuminator, and one or more processors. The processors may be configured to activate the illuminator to illuminate the holographic film and capture, with the image sensor, an image of at least a portion of the holographic film while the holographic film is illuminated. The processors may also be configured to determine a characteristic of the holographic film based on the image and determine, based on the characteristic, a location or an orientation of the image sensor relative to the holographic film. The processors may further be configured to change, based on the location or the orientation of the image sensor relative to the holographic film, at least one calibration parameter of the image sensor.

Abstract: A computer-implemented method of localizing an image of a person captured using a camera is provided, the person in the field of view of a camera, comprising: obtaining the image captured using a camera, the image comprising the person within a bounding box; determining at least one slant value associated with the person within the bounding box; determining head image coordinates and feet image coordinates for the person using the at least one slant value; and localizing the person by projecting the head image coordinates to a head plane and the feet image coordinates for the person to a ground plane.

Abstract: A computer-implemented method for focal length validation may include receiving, by a computing system, initial image data for an optical target from a camera. The method may also include determining a distortion parameter associated with the camera, based on the initial image data. The method may also include receiving, by the computing system, a first image of the optical target, wherein the first image is associated with a first position of the camera. The method may also include receiving, by the computing system, a second image of the optical target, wherein the second image is associated with a second position of the camera. The method may also include determining an estimated displacement between the first position of the camera and the second position of the camera based on the first image and the second image. The method may further include determining a focal length based on the estimated displacement and a measured displacement of the camera between the first position and the second position.

Abstract: An imaging device includes pixel sensors. A drive-sense circuit is configured to generating a sensed signal corresponding to one of pixel sensors. The drive-sense circuit includes: a first conversion circuit configured to convert, a receive signal component of a sensor signal corresponding to the one of the pixel sensors into the sensed signal, wherein the sensed signal indicates a change in a capacitance associated with the one of the pixel sensors; a second conversion circuit configured to generate, based on the sensed signal, a drive signal component of the sensor signal corresponding to the one of the pixel sensors. The drive-sense circuit is further configured to generate other sensed signals corresponding to other ones of the pixel sensors for the other ones of the pixel sensors. A graphics processing module is configured to generate image data based on the sensed signal and the other sensed signals.

Abstract: An electronic device and method for 3D modeling based on 2D warping is disclosed. The electronic device acquires a color image of a face of a user, depth information corresponding to the color image, and a point cloud of the face. A 3D mean-shape model of a reference 3D face is acquired, and rigid aligned with the point cloud. A 2D projection of the aligned 3D mean-shape model is generated. The 2D projection includes a set of landmark points associated with the aligned 3D mean-shape model. The 2D projection is warped such that the set of landmark points in the 2D projection is aligned with a corresponding set of feature points in the color image. A 3D correspondence between the aligned 3D mean-shape model and the point cloud is determined for a non-rigid alignment of the aligned 3D mean-shape model, based on the warped 2D projection and the depth information.

Abstract: An image signal processor and an image sensor including the same are disclosed. An image sensor includes a pixel array configured to convert received optical signals into electrical signals, a readout circuit configured to convert the electrical signals into image data and output the image data, and an image signal processor configured to perform deep learning-based image processing on the image data based on training data selected from among first training data and second training data based on a noise level of the image data.

Abstract: An improved method, system, and apparatus is provided to perform camera calibration, where cameras are mounted onto a moving conveyance apparatus to capture images of a multi-planar calibration target. The calibration process is optimized by reducing the number of images captured while simultaneously preserving overall information density.

Abstract: An imaging device includes an imaging unit that generates image data on the basis of a first power voltage, an image processing unit that performs image processing on the image data on the basis of a second power voltage, a reference voltage generating unit that generates a first reference voltage on the basis of the first power voltage, and a first flag generating unit that generates a first flag signal for the second power voltage on the basis of a comparison of the second power voltage and the first reference voltage and outputs the first flag signal.

Abstract: A method of characterizing an imaging device includes calibrating the imaging device by collecting readings for regular pixels and at least one sealed pixel of the imaging device over one or more periods of time for a sequence of integration time (T) and a plurality of number of lines (NOL) when no light enters the imaging device, obtaining a dark level (DL) by averaging the readings for the regular pixels over the respective period of time and the number of the regular pixels, and obtaining P by averaging the readings of the at least one sealed pixel over the respective period of time and the number of the at least one sealed pixel. A relation between DL and P is determined for each T and NOL using an equation: DL=A*P+Offset. A current value of DL is determined by using a current value of P and the equation.

Abstract: A mobile device for an authentication system that performs authentication to control an authentication target with code verification via near field wireless communication, includes: an acceleration sensor; a communication portion that performs the near field wireless communication with an antenna of the authentication target; a reception stop portion that stops reception operation of the communication portion; a fault detection portion that detects a failure in the acceleration sensor; and an operation change portion that prevents the reception stop portion from stopping the reception operation.

Abstract: An image recognition apparatus includes a processing circuit and a control circuit. The processing circuit receives a first image obtained by performing multiple-exposure image capturing of a first subject. The processing circuit uses the first image to calculate a recognition accuracy of the first subject. The control circuit changes a condition of the multiple-exposure image capturing in a case where the recognition accuracy is lower than a recognition accuracy threshold.

Abstract: A processor may process a video feed of a monitored area. The processing may include attempting to decrypt the video feed using a temporally-varying digital rights management key in a state corresponding to a time at which the encrypted video feed was received and encountering a decryption error during the attempting. The processing may include comparing the video feed with an output feed from a secondary sensor to determine that at least one object is indicated in the monitored area by the output feed and not visible in the video feed. The processor may indicate a problem with the video feed. For example, the processor may indicate that the encrypted video feed has been altered prior to the receiving of the encrypted video feed due to the decryption error and/or that the video camera is malfunctioning due to the at least one object being not visible in the video feed.

Abstract: An information processing apparatus simulates a measurable region of a sensor when the sensor is arranged in a measurement region to be measured, and the information processing apparatus includes: a generation unit that generates a measurement region map with environment information based on a three-dimensional model of the measurement region to be measured and the environment information that causes a change in a measurement result of the sensor; an execution unit that virtually arranges the sensor on the measurement region map with environment information generated by the generation unit, and simulates the measurable region of the sensor based on sensor information related to the measurable region of the sensor; and an output unit that outputs a result of simulation by the execution unit.

Abstract: A method for calibrating an image capturing sensor including at least one sensor camera using a time coded pattern target including: displaying the target on a flat screen display, displaying a pattern sequence on the display and capturing the pattern sequence by the at least one sensor camera as a sequence of a camera images, performing an association between pixels of the target and captured image points of the camera images for at least one fixed position of the display in space or respectively for at least two different positions of the display in space, performing the calibration through corresponding points, performing a gamma correction wherein a gamma curve of the display is captured and corrected in any position of the display and/or in addition to capturing the pattern sequence in any position of the display by the at least one sensor camera before displaying the target.

Abstract: A method and system for determining poses for camera calibration is presented. The system determines a range of pattern orientations for performing the camera calibration, and determines a surface region on a surface of an imaginary sphere, which represents possible pattern orientations for the calibration pattern. The system determines a plurality of poses for the calibration pattern to adopt. The plurality of poses may be defined by respective combinations of a plurality of respective locations within the camera field of view and a plurality of respective sets of pose angle values. Each set of pose angle values of the plurality of respective sets may be based on a respective surface point selected from within the surface region on the surface of the imaginary sphere. The system outputs a plurality of robot movement commands based on the plurality of poses that are determined.