Abstract: Embodiments disclosed herein relate to image prioritization in a collage shape. In one embodiment, image positions are determined within a collage shape based on an importance level map of the collage shape and priorities of the images to be positioned within the collage shape. A collage may be created with the collage images in the determined positions.

Abstract: Photos taken by a user over a period of time are accessed to obtain a location history and visual features of the photos. A user profile is generated from the location history and the visual features. Recommendations are provided to the user based on at least one of the location history and the user profile.

Abstract: A method and system for clustering images, comprising detecting faces in respective images to generate face data, generating a first cluster of images using the face data, the first cluster comprising images with a common face and representing a corresponding person, generating a second cluster of images using clothes data representing a set of clothing signatures, the second cluster comprising images with a common set of clothes, and using the first and second clusters to link an image of the person to the clusters in order to generate a third cluster for the person.

Abstract: Examples disclosed herein relate to clothing stripe detection based on line segment orientation. A processor may determine whether a clothing region within an image includes stripes based on a stripe classifier applied to line segment information about line segments in the clothing region. The line segment information may include the number of line segments in the clothing region at each of a plurality of orientations.

Abstract: Information relating to an exclusion zone to be provided on a page is received (102), where the exclusion zone defines a corresponding area of the page that is free of content to be inserted in the page. A layout defining plural partitions on the page is produced (104), where the layout includes the exclusion zone and the content having a plurality of elements that are inserted by recursively defining the plural partitions on the page, where the exclusion zone and content elements are provided in respective ones of the plural partitions, and where recursively defining the plural partitions considers presence of the exclusion zone.

Abstract: According to an example, a method for object segmentation may include receiving a digital image, performing initial segmentation on the digital image to generate a segmented digital image, and receiving refinement instructions to refine the initial segmentation. The method may further include inferring an intention of a user to correct a foreground area or a background area of the initial segmentation based on the received refinement instructions, learning a behavior of the user to further infer the intention of the user to correct the foreground area or the background area, and refining, by a processor, the initial segmentation based on the inferred intention.

Abstract: Embodiments disclosed herein relate to image prioritization in a collage shape. In one embodiment, image positions are determined within a collage shape based on an importance level map of the collage shape and priorities of the images to be positioned within the collage shape. A collage may be created with the collage images in the determined positions.

Abstract: The disclosure relates to a system and a method for generating clothing feature data representative of at least one clothing feature of a piece of clothing being worn by the person in a set of images, and training a discriminative clothing classifier using the clothing feature data to provide a personal clothing model that corresponds to the piece of clothing. The personal clothing model can be used to identify additional images in which the person appears.

Abstract: A method performed by a physical computing system for determining a layout of graphic objects (802) according to a layout density map (300) includes generating the layout density map (300), the layout density map (300) having low density regions (302) and high density regions (304); providing a set of candidate locations (402) within the layout density map (302), a number of the candidate locations (402) being equal to a number of the graphic objects (802), the candidate locations (402) being arranged away from the low density regions (302) and from other the candidate locations (402); and overlaying the layout density map (300) with the graphic objects (402), each graphic object (802) being disposed at one of the candidate locations (402).

Abstract: An input image (7) having a first pixel resolution is acquired from an image capture system (2). A respective characterization of each of at least one visual quality feature of the input image (7) is determined. An output thumbnail image (9) is produced from the input image (7). The output thumbnail image (9) reflects the respective characterization of each visual quality feature. The output thumbnail image (9) has a second pixel resolution lower than the first pixel resolution. The output thumbnail image (9) is output in association with operation of the image capture system (2).

Abstract: Examples disclosed herein relate to creating an image collage in a semantic theme based shape. For example, a processor may determine a semantic theme associated with an image collection, select a shape associated with the semantic theme, and create a collage of at least a subset of the image collection in the selected shape. The processor may output the created collage.

Abstract: A method of displaying an image with a display device having at least one defective display pixel is provided. The method comprises generating first, second, and third sub-frames using image data for the image, information that identifies the at least one defective display pixel, a first pixel offset associated with the second sub-frame, and a sub-pixel offset associated with the third sub-frame, and alternating between displaying the first sub-frame in a first position, displaying the second sub-frame in a second position spatially offset from the first position according to the first pixel offset, and displaying the third sub-frame in a third position spatially offset from the first position and the second position according to the sub-pixel offset.

Abstract: Examples disclose a method executed on a computing device to locate a clothing region within an image to segment into a region of related clothing. Further, the examples provide detecting a feature of the related clothing. Additionally, the examples also disclose determining a style of the related clothing in the region based on the detection of the feature.

Abstract: A method of quantifying social affinity from multiple images includes identifying each image showing both a first person and a second person and determining a weighted affinity value between the first person and the second person. The weighted affinity value is determined based on a total number of persons appearing in each identified image, a physical distance between the first person and the second person represented in each identified image, and a total number of identified images.

Abstract: In a method of processing a super-resolution target image from a plurality of substantially low resolution auxiliary frames, the target image is partitioned into a plurality of adaptively sized blocks, which are sized based upon registration confidence levels of the blocks obtained from information contained in the plurality of auxiliary frames. The blocks are classified into a plurality of different categories according to one or both of their respective registration confidence levels and their respective variance levels. In addition, separate enhancement modes designed to enhance the blocks are selected according to their respective classifications and applied on the blocks to enhance the target image.

Abstract: Methods, devices, and systems for determining feature descriptors are provided. An example includes defining a plurality of anchor points within a patch of pixels in a particular area that includes a detected feature in an image, defining a first set of subpatches and calculating an intensity of each of the first set of subpatches, defining a second set of subpatches and calculating an intensity of each of the second set of subpatches, comparing the intensity of each of the second set of subpatches to the intensity of each of the first set of subpatches and if the intensity of a second set subpatch is higher than the intensity of a first set subpatch assign a binary value, otherwise assign an alternative binary value, and concatenating all the assigned binary values into a binary feature descriptor.

Abstract: Examples disclose a method executed on a computing device to locate a clothing region within an image to segment into a region of related clothing. Further, the examples provide detecting a feature of the related clothing. Additionally, the examples also disclose determining a style of the related clothing in the region based on the detection of the feature.

Abstract: A method includes determining a target layout in which secondary images (504) are placed along an edge (506, 508) of a primary image (502), dividing each of the secondary images (504) into one of a horizontal group and a vertical group according to the target layout and dimensions of each of the secondary images (504), dividing any of the secondary images (504) in the horizontal group into one of a top group (706) and a bottom group (708) according to the target layout and a width of each of the secondary images (504) in the horizontal group, dividing any of the secondary images (504) of the vertical group into one of a left group and a right group according to the target layout and a height of each of the secondary images (504) in the vertical group, and placing each of the secondary images (504) adjacent to an edge (506, 508) of the primary image (502) according to an assigned group of each secondary image (504).

Abstract: A method and system for clustering images, comprising detecting faces in respective images to generate face data, generating a first cluster of images using the face data, the first cluster comprising images with a common face and representing a corresponding person, generating a second cluster of images using clothes data representing a set of clothing signatures, the second cluster comprising images with a common set of clothes, and using the first and second clusters to link an image of the person to the clusters in order to generate a third cluster for the person.

Abstract: A system and a method are provided for determining an estimated age of an individual of interest based on images in an image collection. An example system includes a memory for storing computer executable instructions, and a processing unit for accessing the memory and executing the computer executable instructions. The computer executable instructions include an age class estimator to classify a plurality of images of the individual into age classes, each age class corresponding to an interval of age, and each image having a known time stamp, a probability determination engine to determine, for each age class, a value of class probability that an image in the collection falls within the age class, an age determination engine to determine a transition time based on the values of class probability and the known time stamp, and to determine the estimated age of the individual based on the determined transition time.