Patent application number | Description | Published |
20110085728 | DETECTING NEAR DUPLICATE IMAGES - Near duplicate images are detected based on local structure feature matching of local features that are extracted from the images. The matching process also may involve detecting near duplicate images based on metadata features and global image features. A computation-sensitive cascaded classifier may be used together with an on-demand feature extraction to detect near duplicate images with improved efficiency and reduced computational cost. | 04-14-2011 |
20110292219 | APPARATUS AND METHODS FOR IMAGING SYSTEM CALIBRATION - A reference set of image features is determined from an electronic data file specifying a reference image in a reference coordinate space. Rendering information describing a physical rendering of the reference image is ascertained. Calibration-enabling data is derived from the reference set of the image features and the ascertained rendering information. The calibration-enabling data is provided to calibrate an imaging system. The calibration-enabling data may be stored. The imaging system may capture an image of the physical rendering of the reference image in relation to a capture coordinate space. An extracted set of image features may be extracted from the captured image. Respective ones of the image features in the reference and extracted sets may be matched. The imaging system may be calibrated based on matched ones of the image features and the rendering information. | 12-01-2011 |
20120076423 | NEAR-DUPLICATE IMAGE DETECTION - A system and a method for near-duplicate image detection performed by a physical computing system includes applying a feature determining function to a number of images, a feature being defined by a geometric shape, comparing characteristics of said geometric shapes defining said features from at least two of said number of images, and characterizing said at least two of said number of images as a near-duplicate match if a predetermined percentage of said features of said at least two images match. | 03-29-2012 |
20120093408 | ORDINAL AND SPATIAL LOCAL FEATURE VECTOR BASED IMAGE REPRESENTATION - A local image patch identified in an image is divided into respective sub-patches of respective image forming elements. For each of the respective image forming elements in the local image patch, a respective ordinal rank of the image forming element is determined, and respective contributions of the image forming element to a particular one of the respective sub-patches containing the image forming element and to one or more other ones of the respective sub-patches neighboring the particular sub-patch are ascertained. Each ordinal rank corresponds to a respective dimension of an ordinal rank feature space. For each of the respective sub-patches of the local image patch, a respective histogram of ascertained contributions of the image forming elements in the ordinal rank feature space is built. A respective feature vector representing the local image patch is generated from the respective histograms built for the sub-patches of the local image. | 04-19-2012 |
20120106854 | EVENT CLASSIFICATION OF IMAGES FROM FUSION OF CLASSIFIER CLASSIFICATIONS - A system and a method are disclosed that classify images according to their association with an event. Both metadata and visual content of images in a collection of images can be used for event classification. The confidence scores from the classification using a metadata classifier and from the classification using a visual classifier are combined through a confidence-based fusion to provide the classification for a set of images. | 05-03-2012 |
20120328167 | MERGING FACE CLUSTERS - A method for merging face clusters includes analyzing a set of digital images, grouping instances of faces within the set of digital images into a set of face clusters, each of the face clusters corresponding to a particular person, and determining a probability that a person associated with a first face cluster from the set of face clusters is the same person associated with a second face cluster of the set of face clusters. The probability is based on both a social similarity between the first face cluster and the second face cluster in addition to a facial similarity between the first face cluster and the second face cluster. | 12-27-2012 |
20120328184 | OPTICALLY CHARACTERIZING OBJECTS - Systems and methods are provided for optically characterizing an object. A method includes querying an image search engine for the object; extracting image features from multiple images returned by the search engine in response to the query; clustering the image features extracted from the images returned by the search engine according to similarities in optical characteristics of the image features; and determining a set of image features most representative of the object based on the clustering. | 12-27-2012 |
20130094780 | Replacement of a Person or Object in an Image - Disclosed herein are a system and a method that use a background model to determine and to segment target content from an image and replace them with different content to provide a composite image. The background model can be generated based on image data representing images of a predetermined area that does not include traversing content. The background model is compared to image data representing a set of captured images of the predetermined area. Based on the comparison, portions of an image that differs from the background model are determined as the traversing content. A target content model is used to determine the target content in the traversing content. The target content determined in the images is replaced with different content to provide a composite image. | 04-18-2013 |
20130100296 | MEDIA CONTENT DISTRIBUTION - A method of distributing media content includes capturing an image of a static media content, detecting at least one feature in the image, seeking a correlation of the image to a reference image using the at least one feature, and identifying at least one region of dynamic media content of the reference image in the image of the static media content. | 04-25-2013 |
20130101226 | FEATURE DESCRIPTORS - 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. | 04-25-2013 |
20130257906 | Generating publication based on augmented reality interaction by user at physical site - Interaction data represents augmented reality interaction by a user using a mobile computing device with physical points of interest at a physical site. A publication is generated based on this interaction data and provided to the user. | 10-03-2013 |
20130259374 | IMAGE SEGMENTATION - In one implementation, an image segmentation system defines a first discriminative classifier and a second discriminative classifier. The first discriminative classifier is associated with a first segment of an object in an image based on a first foreground sample region of the image and a first background sample region of the image. The second discriminative classifier is associated with a second segment of the object based on a second foreground sample region of the image and a second background sample region of the image. The image segmentation system then identifies at least a portion of the first segment using the first discriminative classifier and at least a portion of the second segment using the second discriminative classifier. | 10-03-2013 |
20140029854 | METADATA SUPERSETS FOR MATCHING IMAGES - A method for creating and using metadata supersets for matching images includes identify images from a first source of images and identify images from a second source of images. Images from the first source that match images from the second source are identified as matching images. Metadata associated with the matching images are extracted to form a superset of metadata for the matching images. The superset of metadata is analyzed to create a product. | 01-30-2014 |