Abstract: Image distractor detection and processing techniques are described. In one or more implementations, a digital medium environment is configured for image distractor detection that includes detecting one or more locations within the image automatically and without user intervention by the one or more computing devices that include one or more distractors that are likely to be considered by a user as distracting from content within the image. The detection includes forming a plurality of segments from the image by the one or more computing devices and calculating a score for each of the plurality of segments that is indicative of a relative likelihood that a respective said segment is considered a distractor within the image. The calculation is performed using a distractor model trained using machine learning as applied to a plurality images having ground truth distractor locations.

Abstract: Variable patch shape synthesis techniques are described. In one or more implementations, a plurality of patches are computed from one or more images, at least one of the plurality of patches having a different shape than another one of the plurality of patches. The shapes define an area to be considered for use in a patch synthesis technique. The patch synthesis technique is performed to edit an image using the computed plurality of patches having the different shapes.

Abstract: Techniques for focal length warping are described. Focal length warping, for instance, may provide an automated approach for correcting distortion in an input image to improve its perceptual quality. In at least some implementations, a focal length of a camera lens used to capture an image and an estimated camera distance are utilized to three-dimensionally reproject and warp the image to generate an adjusted image simulating a new focal length and a new camera distance. Implementations of focal length warping may estimate a camera distance based on facial features in an image.

Abstract: Image distractor detection and processing techniques are described. In one or more implementations, a digital medium environment is configured for image distractor detection that includes detecting one or more locations within the image automatically and without user intervention by the one or more computing devices that include one or more distractors that are likely to be considered by a user as distracting from content within the image. The detection includes forming a plurality of segments from the image by the one or more computing devices and calculating a score for each of the plurality of segments that is indicative of a relative likelihood that a respective said segment is considered a distractor within the image. The calculation is performed using a distractor model trained using machine learning as applied to a plurality images having ground truth distractor locations.

Abstract: Image distractor detection and processing techniques are described. In one or more implementations, a digital medium environment is configured for image distractor detection that includes detecting one or more locations within the image automatically and without user intervention by the one or more computing devices that include one or more distractors that are likely to be considered by a user as distracting from content within the image. The detection includes forming a plurality of segments from the image by the one or more computing devices and calculating a score for each of the plurality of segments that is indicative of a relative likelihood that a respective said segment is considered a distractor within the image. The calculation is performed using a distractor model trained using machine learning as applied to a plurality images having ground truth distractor locations.

Abstract: Techniques for focal length warping are described. Focal length warping, for instance, may provide an automated approach for correcting distortion in an input image to improve its perceptual quality. In at least some implementations, a focal length of a camera lens used to capture an image and an estimated camera distance are utilized to three-dimensionally reproject and warp the image to generate an adjusted image simulating a new focal length and a new camera distance. Implementations of focal length warping may estimate a camera distance based on facial features in an image.

Abstract: Image distractor detection and processing techniques are described. In one or more implementations, a digital medium environment is configured for image distractor detection that includes detecting one or more locations within the image automatically and without user intervention by the one or more computing devices that include one or more distractors that are likely to be considered by a user as distracting from content within the image. The detection includes forming a plurality of segments from the image by the one or more computing devices and calculating a score for each of the plurality of segments that is indicative of a relative likelihood that a respective said segment is considered a distractor within the image. The calculation is performed using a distractor model trained using machine learning as applied to a plurality images having ground truth distractor locations.

Abstract: Methods, apparatus, and computer-readable storage media for patch-based image synthesis using color and color gradient voting. A patch matching technique provides an extended patch search space that encompasses geometric and photometric transformations, as well as color and color gradient domain features. The photometric transformations may include gain and bias. The patch-based image synthesis techniques may also integrate image color and color gradients into the patch representation and replace conventional color averaging with a technique that performs voting for colors and color gradients and then solves a screened Poisson equation based on values for colors and color gradients when blending patch(es) with a target image.

Abstract: Variable patch shape synthesis techniques are described. In one or more implementations, a plurality of patches are computed from one or more images, at least one of the plurality of patches having a different shape than another one of the plurality of patches. The shapes define an area to be considered for use in a patch synthesis technique. The patch synthesis technique is performed to edit an image using the computed plurality of patches having the different shapes.

Abstract: Methods, apparatus, and computer-readable storage media for patch-based image synthesis using color and color gradient voting. A patch matching technique provides an extended patch search space that encompasses geometric and photometric transformations, as well as color and color gradient domain features. The photometric transformations may include gain and bias. The patch-based image synthesis techniques may also integrate image color and color gradients into the patch representation and replace conventional color averaging with a technique that performs voting for colors and color gradients and then solves a screened Poisson equation based on values for colors and color gradients when blending patch(es) with a target image.

Abstract: Techniques for determining correspondence between image regions are described. A computing system stores images that are comparable to determine corresponding image patches of the images. An approximation algorithm is implemented, and for multiple image patches in a region in a first image, corresponding image patches are determined in a second image. The approximation algorithm performs iterations utilizing a nearby-pixel mapping evaluation and a random-perturbation mapping evaluation to determine and select the corresponding image patches in the second image.

Abstract: Methods, apparatus, and computer-readable storage media for patch-based image synthesis. A patch matching technique provides an extended patch search space that encompasses geometric and photometric transformations, as well as gradient domain features. The geometric transformations may include translation, rotation, reflection, scale, and non-uniform scale. The photometric transformations may include gain and bias. Patch-based image synthesis techniques may leverage the extended patch search space in various image synthesis applications. The patch-based image synthesis techniques may also integrate image gradients into the patch representation and replace conventional color averaging with a technique that performs voting for colors and gradients and then solves a screened Poisson equation based on values for colors and gradients when blending patch(es) with a target image.

Abstract: Techniques for determining correspondence between image regions are described. A computing system stores images that are comparable to determine corresponding image patches of the images. An approximation algorithm is implemented, and for multiple image patches in a region in a first image, corresponding image patches are determined in a second image. The approximation algorithm performs iterations utilizing a nearby-pixel mapping evaluation and a random-perturbation mapping evaluation to determine and select the corresponding image patches in the second image.

Abstract: Methods and systems for creating an image filter is described. In one embodiment, a method includes receiving a first plurality of images captured by an at least one camera with a same setting as a first camera. The method further includes creating an averaged image from the plurality of captured images, wherein the averaged image comprises a measurement value of intensity for each pixel in the averaged image. The method also includes determining an image imperfection in the averaged image. The method further includes creating the image filter to reduce the image imperfection.

Abstract: Methods and apparatus for generating context-sensitive, co-salient thumbnails are described. Co-salient thumbnails may effectively convey more useful information than conventional thumbnails while using the same or similar display space. As such, co-salient thumbnails may make it easier for a user to locate a particular image in a large collection of similar images. In some embodiments, for each of a plurality of patches in a first image, an illustrative method may identify a corresponding similar patch in a second image based on one or more similarity measures. The method may then determine a distance from each of the plurality of patches to its corresponding similar patch and select a crop in the first image relative to the second image based on the determined distance. Optionally, the method may repeat these operations in the opposite direction to select a crop in the second image relative to the first image.

Abstract: Methods and apparatuses for generating thumbnail summaries for image collections are described. Thumbnails summaries may be representative of the image collection while being disjoint from each other. In some embodiments, a method may sample crops from some or all images in an image collection. From these candidate crops, the method may select representative but disjoint crops. In some embodiments, a desired representativeness and/or disjointedness of the candidate crops may be defined by a user. The method may then generate and/or select thumbnail summaries for the collection of images based at least in part on the selected candidate crops.

Abstract: Methods and apparatuses for generating thumbnail summaries for image collections are described. Thumbnails summaries may be representative of the image collection while being disjoint from each other. In some embodiments, a method may sample crops from some or all images in an image collection. From these candidate crops, the method may select representative but disjoint crops. In some embodiments, a desired representativeness and/or disjointedness of the candidate crops may be defined by a user. The method may then generate and/or select thumbnail summaries for the collection of images based at least in part on the selected candidate crops.

Abstract: Methods and apparatus for generating context-sensitive, co-salient thumbnails are described. Co-salient thumbnails may effectively convey more useful information than conventional thumbnails while using the same or similar display space. As such, co-salient thumbnails may make it easier for a user to locate a particular image in a large collection of similar images. In some embodiments, for each of a plurality of patches in a first image, an illustrative method may identify a corresponding similar patch in a second image based on one or more similarity measures. The method may then determine a distance from each of the plurality of patches to its corresponding similar patch and select a crop in the first image relative to the second image based on the determined distance. Optionally, the method may repeat these operations in the opposite direction to select a crop in the second image relative to the first image.

Abstract: Methods, apparatus, and computer-readable storage media for patch-based image synthesis. A patch matching technique provides an extended patch search space that encompasses geometric and photometric transformations, as well as gradient domain features. The geometric transformations may include translation, rotation, reflection, scale, and non-uniform scale. The photometric transformations may include gain and bias. Patch-based image synthesis techniques may leverage the extended patch search space in various image synthesis applications. The patch-based image synthesis techniques may also integrate image gradients into the patch representation and replace conventional color averaging with a technique that performs voting for colors and gradients and then solves a screened Poisson equation based on values for colors and gradients when blending patch(es) with a target image.

Abstract: Methods and apparatus for camera calibration based on multiview image geometry. A lens profiling module may estimate two or more mathematical models for correcting aberrations in images in a single pass from a set of calibration images captured with a camera/lens combination. For example, the module may estimate the lens aberrations of geometric distortion, lateral chromatic aberration, and vignette models in a single pass. The module may determine point correspondences, 3D transformations, and camera intrinsics for views of calibration charts captured in the images. The module estimates the mathematical models for the two or more types of aberrations from the information determined from the views of the calibration charts. The module may automatically determine an optimal model complexity when estimating the mathematical models. The estimated models may be written or appended to a lens profile for the camera/lens combination used to captured the calibration images.