Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for associating still images and videos. One method includes receiving a plurality of images and a plurality of videos and determining whether the images are related to the videos. The determining includes, for an image and a video, extracting features from the image and extracting features frames of the video, and comparing the features to determine whether the image is related to the video. The method further includes maintaining a data store storing data associating each image with each video determined to be related to the image.

Abstract: Described is a system and method for enabling dynamic selection of a search input. For example, rather than having a static search input box, the search input may be dynamically positioned such that it encompasses a portion of displayed information. An image segment that includes a representation of the encompassed portion of the displayed information is generated and processed to determine an object represented in the portion of the displayed information. Additional images with visually similar representations of objects are then determined and presented to the user.

Abstract: Co-selected images are labeled based on a topic score that is a measure of relevance of the co-selected image to a first topic to which a reference image belongs. The first topic to which the reference image belongs is identified based on a reference label associated with the reference image. The co-selected images are images that are selected for presentation subsequent to selection of the reference image during a user session. The co-selected images are identified based on selection data for user sessions in which the reference image was selected for presentation. The topic score is generated based on a frequency of selection of the co-selected image. Image search results for a second topic can be filtered to remove images that are labeled as belonging to the first topic or the image search results can be reordered to adjust the presentation positions at which images are referenced based on the topic to which the images belong.

Abstract: Methods, systems, and articles of manufacture for annotating of an image are disclosed. These include scoring the image using a plurality of trained classifiers, wherein each of the trained classifiers corresponds to at least one of a plurality of image groups clustered based upon image similarity, and wherein each image group is associated with a set of weighted labels; selecting one or more of the image groups based upon the scoring; aggregating one or more sets of weighted labels associated with the selected one or more image groups; and annotating the image using the aggregated one or more sets of weighted labels.

Abstract: Image similarity operations are performed in which a seed image is analyzed, and a set of semantic classifications are determined from analyzing the seed image. The set of semantic classifications can include multiple positive semantic classifications. A distance measure is determined that is specific to the set of semantic classifications. The seed image is compared to a collection of images using the distance measure. A set of similar images is determined from comparing the seed image to the collection of images.

Abstract: Systems and methods are disclosed for determining the location where an image was captured. In general, a device such as a smartphone may capture one or more images from a location, such as images of buildings, street signs and the like, and a central system may compare the submitted images to images in an image library to identify matches. The location of the match may then be provided back to the smartphone.

Abstract: Aspects of the subject matter described herein relate to functions used for retrieving image results based on search queries. More specifically, image search queries can be pre-grouped or classified based on visual and semantic similarity. For example, a pairwise image similarity value for a pair of queries can be computed based on one or more of the sum of all of the overlapping the image results, the sum of the image distances between all of the pairs of images in the image results, and the rank of each of the images in the image results. The pairwise image similarity values can then be used to generate image query clusters. Each image query clusters can include a set of queries with high pairwise image similarity values. In some examples, a distance function can be determined for each image query cluster. This data can be used to provide image results.

Abstract: The subject matter of this specification can be embodied in, among other things, a computer-implemented method that includes receiving a plurality of images having human faces. The method further includes generating a data structure having representations of the faces and associations that link the representations based on similarities in appearance between the faces. The method further includes outputting a first gender value for a first representation of a first face that indicates a gender of the first face based on one or more other gender values of one or more other representations of one or more other faces that are linked to the first representation.

Abstract: Methods, systems, and apparatus, including computer program products are provided for ranking distinct book content items based on implicit links to other distinct book content items. The implicit links are defined based on the identification of matching features in the distinct book content items. In some implementations, the matching features are uncommon phrases in textual content of the distinct book content items. Edges representing implicit links are generated between distinct nodes representing distinct book content items in a weighted graph. Search results for distinct book content items can be ordered based on the edges connected to the distinct nodes in the weighted graph that represent the distinct book content items.

Abstract: Techniques for identifying groups of local features in an image and presenting advertisement information associated with stored images that match one or more features within the group of local features are described. The techniques include providing an image, identifying a region of interest in the image, providing a user-selectable link associated with the region of interest in the image, receiving a request for the region of interest in the image via the user-selectable link, and presenting advertisement information associated with a stored image that matches one or more features within the requested region of interest.

Abstract: Implementations consistent with the principles described herein relate to ranking a set of images based on features of the images determine the most representative and/or highest quality images in the set. In one implementation, an initial set of images is obtained and ranked based on a comparison of each image in the set of images to other images in the set of images. The comparison is performed using at least one predetermined feature of the images.

Abstract: Embodiments for moving object detection in an image are disclosed. These include detecting a moving object in an input image by selecting video frames that are visually similar to the input image, generating a model motion image by estimating motion for each selected video frame, and detecting, using the model motion image, a moving object in the input image based on differences between the model motion image and the input image.

Abstract: A device may be configured to identify a plurality of images that are similar to a query image; generate a plurality of sets of rankings of the identified images based on a plurality of image attributes; compare the generated plurality of sets of rankings of the identified images to a reference set of rankings of images; select, based on the comparing, a particular set of rankings; and rank a plurality of images that are associated with another query image, based on an attribute associated with the selected particular set of rankings.

Abstract: In some implementations, a computer-implemented method is provided that includes accessing a database of career path data structures, each career path data structure including an initial node that represents an initial career position, a subsequent node that represents a subsequent career position, and a path element that represents a career transition between the initial career position and the subsequent career position and is associated with data regarding people that have made the career transition between the initial career position and the subsequent career position. The method includes receiving a career path query. The method includes identifying a set of the career path data structures based on the career path query. The method includes generating a set of career paths from the career path data structures, each career path including a directed graph that includes two or more nodes. The method includes providing a representation of the set of career paths.

Abstract: This specification relates to presenting image search results. In general, one aspect of the subject matter described in this specification can be embodied in methods that include the actions of receiving an image query, the image query being a query for image search results; receiving ranked image search results responsive to the image query, the image search results each including an identification of a corresponding image resource; generating a similarity matrix for images identified by the image search results; generating a hierarchical grouping of the images using the similarity matrix; identifying a canonical image for each group in the hierarchical grouping using a ranking measure; and presenting a visual representation of the image search results based on the hierarchical grouping and the identified canonical images.

Abstract: Systems and methods are disclosed for determining the location where an image was captured. In general, a device such as a smartphone may capture one or more images from a location, such as images of buildings, street signs and the like, and a central system may compare the submitted images to images in an image library to identify matches. The location of the match may then be provided back to the smartphone.

Abstract: Methods, systems, and apparatus, including computer program products are provided for ranking distinct book content items based on implicit links to other distinct book content items. The implicit links are defined based on the identification of matching features in the distinct book content items. In some implementations, the matching features are uncommon phrases in textual content of the distinct book content items. Edges representing implicit links are generated between distinct nodes representing distinct book content items in a weighted graph. Search results for distinct book content items can be ordered based on the edges connected to the distinct nodes in the weighted graph that represent the distinct book content items.

Abstract: Techniques for identifying groups of local features in an image and presenting advertisement information associated with stored images that match one or more features within the group of local features are described. The techniques include providing an image, identifying a region of interest in the image, providing a user-selectable link associated with the region of interest in the image, receiving a request for the region of interest in the image via the user-selectable link, and presenting advertisement information associated with a stored image that matches one or more features within the requested region of interest.

Abstract: This specification relates to presenting image search results. In general, one aspect of the subject matter described in this specification can be embodied in methods that include the actions of receiving an image query, the image query being a query for image search results; receiving ranked image search results responsive to the image query, the image search results each including an identification of a corresponding image resource; generating a similarity matrix for images identified by the image search results; generating a hierarchical grouping of the images using the similarity matrix; identifying a canonical image for each group in the hierarchical grouping using a ranking measure; and presenting a visual representation of the image search results based on the hierarchical grouping and the identified canonical images.

Abstract: Implementations consistent with the principles described herein relate to ranking a set of images based on features of the images determine the most representative and/or highest quality images in the set. In one implementation, an initial set of images is obtained and ranked based on a comparison of each image in the set of images to other images in the set of images. The comparison is performed using at least one predetermined feature of the images.