Abstract: Respective models of visual weight in images are determined. An image query is generated from a determined visual weight distribution. At least one of the images is retrieved from a database based on comparisons of the image query with respective ones of the visual weight models.

Abstract: A method for classifying a video regarding a subjective characteristic, the method comprising: measuring a plurality of basic features (11) per frame thus obtaining a plurality of basic features measurements; creating a plurality of second-level features by pooling (12) said basic features (11) measurements using a plurality of statistics of said basic features measurements in a determined period of time of footage; creating a plurality of video features by pooling (13) said plurality of second-level features using a plurality of statistics of said second level features along the duration of the video; choosing at least one video feature of said plurality of video features for classifying a video regarding a subjective characteristic.

Abstract: Metadata placeholders are used for distributed processing. The metadata placeholders are added to digital objects. The placeholders are filled with requests to perform certain downstream processing on the objects. The placeholders are at least partially empty so they can be filled in by nodes that perform the downstream processing.

Abstract: One embodiment of the present invention provides a method for selecting an image for insertion into a document. A color harmony is received. A document color data of the document is accessed. An image color data of each of a plurality of images is accessed. A harmony measure is determined between the document color data and each of the image color data according to the color harmony.

Abstract: A method that includes classifying photographs into categories; generating computational models of image aesthetics, each computational model of image aesthetics associated to one different category of the categories; extracting a plurality of features from a photograph, the plurality of features including simplicity features, global features computed in the whole image and/or low-level features in contrasting regions of an image of the photograph, the contrasting regions being partitions of the image obtained by applying an image segmentation algorithm based on feature contrast to the photograph; and applying a computational model of image aesthetics to at least part of the plurality of features extracted from the photograph, the computational model applied according to the category of the photograph, in order to assess aesthetic quality of the photograph.

Abstract: A method for classifying an image regarding a certain subjective characteristic, the method comprising: identifying the relevant and accent regions within said image; obtaining a plurality of measurements of image composition features in said image, wherein said image composition features comprises at least one of the following: a feature based on the number of relevant and/or accent regions in said image, a feature based on the homogeneity in the layout of the relevant regions, a feature based on the correlation with the position of said relevant regions within the frame; choosing at least one measurement of said plurality of measurements of image composition features for rating said image on a scale regarding said certain subjective characteristic.

Abstract: In a method of automatically creating a scalable relevance ordered representation of an image collection, the images in the image collection are classified into a plurality of clusters based upon a feature of the images. In addition, respective relevance levels of the images contained in each of the plurality of clusters are determined and the images in each of the plurality of clusters are ordered according to the relevance levels. Moreover, the images from the ordered plurality of clusters are arranged according to a predefined arrangement process to create the scalable relevance ordered representation of the image collection.

Abstract: A method to assess aesthetic quality of photographs, including classifying photographs into categories; generating computational models of image aesthetics, each computational model of image aesthetics associated to one different category of the categories; extracting a plurality of features from a photograph, the plurality of features being simplicity features, global features computed in the whole image and/or low-level features in contrasting regions of an image of said photograph. The contrasting regions are partitions of the image obtained by applying an image segmentation algorithm based on feature contrast to the photograph. The method also including applying a computational model of image aesthetics to at least part of the plurality of features extracted from said photograph, the computational model applied according to the category of the photograph, in order to assess aesthetic quality of the photograph.

Abstract: A method for classifying a video regarding a subjective characteristic, the method comprising: measuring a plurality of basic features (11) per frame thus obtaining a plurality of basic features measurements; creating a plurality of second-level features by pooling (12) said basic features (11) measurements using a plurality of statistics of said basic features measurements in a determined period of time of footage; creating a plurality of video features by pooling (13) said plurality of second-level features using a plurality of statistics of said second level features along the duration of the video; choosing at least one video feature of said plurality of video features for classifying a video regarding a subjective characteristic.

Abstract: A method for providing a visual indication of a content of a video that reflects a likely intent of a user that acquired the video. The present method enables repurposing of a video into a variety of output forms that are adapted to the likely intent of the user and enables more efficient browsing of a stored video.

Abstract: Systems and methods of authoring a multimedia file are described. In one method of authoring a multimedia file, a collection of media objects, including a reference media object of indexed temporally-ordered data structures, is accessed. The reference media object is rendered. While the reference media object is being rendered, a media object in the collection is linked to the reference media object with a rendering time synchronized to the rendering of the reference media object. In another multimedia file authoring method, a collection of inter-linked media objects is accessed. Media objects are sequentially rendered in accordance with a sequence of media object links selected by a user while media objects are being rendered. The sequence of selected media object links and synchronization data are stored to enable reproduction of media object rendering experienced by the user.

Abstract: A method for automatically selecting and organizing a subset of photos from a set of photos provided by a user, who has an account on at least one social network providing some context, for creating a summarized photo album with a storytelling structure. The method comprises: arranging the set of photos into a three level hierarchy, acts, scenes and shots; checking whether photos are photos with people or not; obtaining an aesthetic measure of the photos; creating and ranking face clusters; selecting the most aesthetic photo of each face cluster; selecting photos with people until complete a predefined number of photos of the summarized album picking the ones which optimize the function: Of(C,C*,S,CSN)=?fAf(S)??fd(HCharacter(S)HCharacter(C?CSN)??fd(HAct(S),HAct(C*)); and then selecting non-people photos which minimize the following function Oa: Oa(C*,S)=d(HAct,(S),HAct(C*)); ordering all the selected photos in chronological order; and finally discarding all the photos which have not been selected.

Abstract: A respective model of background color is determined for each image in a set of images. For each of the images, a respective background sub-image is extracted from the image, the background sub-image is segmented into regions, and each of the regions is labeled with a respective color label. An image query is generated from a target color template. For each of the images, a respective score is calculated from the image query and the respective color model. At least one of the images is retrieved from an image collection based on the respective scores.

Abstract: A method for automatically selecting and organizing a subset of photos from a set of photos provided by a user, who has an account on at least one social network providing some context, for creating a summarized photo album with a storytelling structure. The method comprises: arranging the set of photos into a three level hierarchy, acts, scenes and shots; checking whether photos are photos with people or not; obtaining an aesthetic measure of the photos; creating and ranking face clusters; selecting the most aesthetic photo of each face cluster; selecting photos with people until complete a predefined number of photos of the summarized album picking the ones which optimize the function: Of(C,C*,S,CSN)=?fAf(S)??fd(HCharacter(S)HCharacter(C?CSN)??fd(HAct(S), HAct(C*)); and then selecting non-people photos which minimize the following function Oa: Oa(C*,S)=d(HAct,(S),HAct(C*)); ordering all the selected photos in chronological order; and finally discarding all the photos which have not been selected.

Abstract: Methods, machines, systems and machine-readable instructions for producing marketing items are described. In one aspect, a user is prompted to specify campaign parameters, including one or more campaign topics, defining a scope of the campaign. The user is prompted to specify for each of the one or more campaign topics a corresponding set of one or more attributes of intended recipients of the marketing campaign. The one or more specified campaign topics are associated to respective sets of targeted recipients selected from a database of records of potential recipients based on mappings of the respective sets of recipient attributes to the campaign topics and the specified campaign parameters defining the scope of the marketing campaign. For each of the targeted recipients, a respective marketing item containing a respective set of one or more contents matched to the campaign topic associated to the targeted recipient is composed.

Abstract: Various disc enhancement systems and methods are disclosed. In some embodiments, methods comprise retrieving information from a master optical disc; retrieving a data structure from a slave optical disc; using the information from the master optical disc to modify the data structure; and playing content from the slave optical disc in accordance with the modified data structure.

Abstract: Image management methods, image management systems, and articles of manufacture are described. According to one embodiment, an image management method includes storing a plurality of images using storage circuitry, storing a plurality of representations for respective ones of the images, and the representations comprise data corresponding to a plurality of human comprehensible words of a human readable lexicon and descriptive of respective characteristics of content of the images, associating respective ones of the representations with respective ones of the respective one of the images, accessing search criteria, comparing the search criteria with the representations, identifying a selected one of the images responsive to the comparing, and accessing the selected one of the images from the storage circuitry responsive to the identifying.

Abstract: For each image in a collection of images, a respective model of visual weight in the image and a respective model of color in the image are determined. An image query is generated from a target visual weight distribution and a target color template. For each of the images a respective score is calculated from the image query, the respective visual weight model, and the respective color model. At least one of the images is retrieved from a database based on the respective scores.

Abstract: Exemplary embodiments of the present invention are directed to a method for automatically selecting images, from among multiple images, for sequential display, comprising: establishing a total time for a sequential display of a set of selected images; clustering images into groups; ordering the images based on image quality; and selecting at least one of the images within a selected group based on the image quality and total time for inclusion in the set of selected images.

Abstract: In a method of automatically creating a scalable relevance ordered representation of an image collection, the images in the image collection are classified into a plurality of clusters based upon a feature of the images. In addition, respective relevance levels of the images contained in each of the plurality of clusters are determined and the images in each of the plurality of clusters are ordered according to the relevance levels. Moreover, the images from the ordered plurality of clusters are arranged according to a predefined arrangement process to create the scalable relevance ordered representation of the image collection.