Canon Kabushiki Kaisha

Matthew Raphael Arnison

David Peter Morgan-Mar

Kieran Gerard Larkin

Peter Alleine Fletcher

Tuan Quang Pham

Ernest Yiu Cheong Wan

Stephen James Hardy

David Robert James Monaghan

Eric Wai-Shing Chong

Steven Richard Irrgang

David Karlov

Allen Peter Courtney

Ruimin Pan

Yoichi Kazama

Christine Anne Deller

Colin Eric Druitt

Thai Quan Huynh-Thu

Timothy Stephen Mason

Juno Kim

Vanessa Jeanie Honson

A system and method determining a camera pose. The method comprises receiving a first image and a second image, the first and second images being associated with a camera pose and a height map for pixels in each corresponding image, and determining a mapping between the first image and the second image using the corresponding height maps, the camera pose and a mapping of the second image to an orthographic view. The method further comprises determining alignment data between the first image transformed using the determined mapping and the second image and determining a refined camera pose based on the determined alignment data and alignment data associated with at least one other camera pose.

System and method for determining a camera pose

A method for processing a three-dimensional graphic object. The method comprises receiving a query point and an associated query region, the query point being positioned within a reference fragment of a texture image of the three-dimensional graphic object; determining reference points on a boundary of the reference fragment using the query region, the reference points associated with target points on a boundary of a target fragment of the texture image, the reference points and the query point forming a reference angle; and determining a portion of the target fragment covered by the query region using an anchor point located outside the target fragment. The anchor point is determined using the target points and the reference angle. Angles between the anchor point and the target points correspond to angles between the query and reference points. The three-dimensional graphic object is processed using the determined portion of the target fragment.

System and method for processing a graphic object

One or more embodiments of an apparatus, system and method of compensating image data for phase fluctuations caused by a wave deforming medium, and storage or recording mediums for use therewith, are provided herein. At least one embodiment of the method comprises capturing, by a sensor of an imaging system, first image data and second image data for each of a plurality of pixel positions of the sensor, the sensor capturing an object through a wave deforming medium causing a defocus disparity between the first image data and second image data; and determining the defocus disparity between the first image data and the second image data, the defocus disparity corresponding to a defocus wavefront deviation of the wave deforming medium. The method may further comprise compensating the image data captured by the sensor for phase fluctuations caused by the wave deforming medium using the determined defocus disparity.

Image processing for turbulence compensation

A method of rendering a graphical object comprises accessing a mapping relating a mesoscale structure and a light scattering parameter of a material to a perceptual appearance characteristic; determining a perceptual appearance characteristic of the graphical object, the graphical object reproduced on an interface to represent an object formed from the material, the perceptual appearance characteristic determined in accordance with the mapping using an initial mesoscale structure and a light scattering parameter of the material; receiving a signal indicating a modification in structure relating to the initial mesoscale structure; and determining, using the mapping, an adjustment of the light scattering parameter preserving the determined perceptual appearance characteristic, based on the modification of the initial mesoscale structure. The method further comprises adjusting the light scattering parameter of the material according to the adjustment; and rendering the graphical object using the modified mesoscale structure and the adjusted light scattering parameter.

System and method of rendering a graphical object with modification in structure

A method of determining at least two motion values of an object moving axially in a scene. A first and second image of the object in the scene is captured with an image capture device. The object is axially displaced in the scene between the captured images with respect to a sensor plane of the image capture device. A variation in blur between the first and second captured images is determined. A scale change of the object between the first and second captured images is determined. Using the determined scale change and variation in blur, at least two motion values of the object in the scene are determined. The motion values identify the depths of the object in the first and second captured images and axial motion of the object in the scene.

Method, system and apparatus for determining distance to an object in a scene

A method of determining a depth value of a fine structure pixel in a first image of a scene using a second image of the scene is disclosed. A gradient orientation for each of a plurality of fine structure pixels in the first image is determined. Difference images are generated from the second image and a series of blurred images formed from the first image, each difference image corresponding to one of a plurality of depth values. Each of the difference images is smoothed, in accordance with the determined gradient orientations, to generate smoothed difference images having increased coherency of fine structure. For each of a plurality of fine structure pixels in the first image, one of the smoothed difference images is selected. The depth value of the fine structure pixel corresponding to the selected smoothed difference image is determined.

Method, system and apparatus for determining a depth value of a pixel

A technique determines a depth measurement associated with a scene captured by an image capture device. The technique receives at least first and second images of the scene, in which the first image is captured using at least one different camera parameter than that of the second image. At least first and second image patches are selected from the first and second images, respectively, the selected patches corresponding to a common part of the scene. The selected image patches are used to determine which of the selected image patches provides a more focused representation of the common part. At least one value is calculated based on a combination of data in the first and second image patches, the combination being dependent on the more focused image patch. The depth measurement of the common part of the scene is determined from the at least one calculated value.

Determining a depth map from images of a scene

Methods, apparatuses, and computer readable storage media are provided for determining a depth measurement of a scene using an optical blur difference between two images of the scene. Each image is captured using an image capture device with different image capture device parameters. A corresponding image patch is identified from each of the captured images, motion blur being present in each of the image patches. A kernel of the motion blur in each of the image patches is determined. The kernel of the motion blur in at least one images patch is used to generate a difference convolution kernel. A selected first image patch is convolved with the generated difference convolution kernel to generate a modified image patch. A depth measurement of the scene is determined from an optical blur difference between the modified image patch and the remaining image patch.

Motion blur compensation for depth from defocus

Disclosed is method of measuring the displacement between a reference region of a reference image and a sample region of a sample image. The method spatially varies the reference region using a one-dimensional filter having complex kernel values, wherein a length (radius) and direction (angle or tangent segment) of the filter is a function of position in the reference region. The method then measures a displacement between the reference region and the sample region by comparing the spatially varied reference region and the sample region.

Estimation of shift and small image distortion

Methods for determining a depth measurement of a scene which involve capturing at least two images of the scene with different camera parameters, and selecting corresponding image patches in each scene. A first approach calculates a plurality of complex responses for each image patch using a plurality of different quadrature filters, each complex response having a magnitude and a phase, assigns, for each quadrature filter, a weighting to the complex responses in the corresponding image patches, the weighting being determined by a relationship of the phases of the complex responses, and determines the depth measurement of the scene from a combination of the weighted complex responses.

A method of modifying the blur in at least a part of an image of a scene captures at least two images of the scene with different camera parameters to produce a different amount of blur in each image. A corresponding patch in each of the captured images is selected each having an initial amount of blur is used to calculate a set of frequency domain pixel values from a function of transforms of the patches. Each of the pixel values in the set are raised to a predetermined power, forming an amplified set of frequency domain pixel values. The amplified set of frequency domain pixel values is combined with the pixels of the patch in one of the captured images to produce an output image patch with blur modified relative to the initial amount of blur in the image patch.

Bokeh amplification

Disclosed is a method of determining at least one three-dimensional (3D) geometric parameter of an imaging device. A two-dimensional (2D) target image is provided having a plurality of alignment patterns. The target image is imaged with an imaging device to form a captured image. At least one pattern of the captured image is compared with a corresponding pattern of the target image. From the comparison, the geometric parameter of the imaging device is then determined. The alignment patterns include at least one of (i) one or more patterns comprising a 2D scale and rotation invariant basis function, (ii) one or more patterns comprising a 1D scale invariant basis function, and (iii) one or more patterns having a plurality of grey levels and comprising a plurality of superimposed sinusoidal patterns, the plurality of sinusoidal patterns having a plurality of predetermined discrete orientations. Also disclosed is a two-dimensional test chart for use in testing an imaging device, the test chart comprising a plurality of alignment patterns, at least one of said alignment patterns including one of those patterns mentioned above.

Geometric parameter measurement of an imaging device

A method of determining a focus parameter for aligning a water in an exposure tool within a measurement tolerance required for the exposure tool, the exposure tool using a lens system for alignment. A test chart is provided having a sharp auto-correlation associated with the wafer. An image of the test chart is captured using a lens pupil mask having at least two phase ramps that are non-parallel. The captured image of the test charge is auto-correlated to determine the position of the test chart relative to a focal position of the lens system. The focus parameter for alignment of the wafer is determined using the determined position of the test chart, whereby the focus parameter is determined within the measurement tolerance required by the exposure tool.

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Umina Beach, Australia

Matthew Raphael Arnison