Canon Kabushiki Kaisha

David Peter Morgan-Mar

Matthew Raphael Arnison

Kieran Gerard Larkin

Peter Alleine Fletcher

Tuan Quang Pham

Stephen James Hardy

Christine Anne Deller

Timothy Stephen Mason

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 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 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

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.

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Wollstonecraft, Australia

David Peter Morgan-Mar