| Patent application number | Description | Published |
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| 20090144033 | OBJECT COMPARISON, RETRIEVAL, AND CATEGORIZATION METHODS AND APPARATUSES - Object comparison is disclosed, including: adapting N universal mixture model components to a first object to generate N corresponding first object mixture model components, where N is an integer greater than or equal to two; and generating a similarity measure based on component-by-component comparison of the N first object mixture model components with corresponding N second object mixture model components obtained by adaptation of the N universal mixture model components to a second object. | 06-04-2009 |
| 20090231355 | COLOR TRANSFER BETWEEN IMAGES THROUGH COLOR PALETTE ADAPTATION - An image adjustment includes adapting a universal palette to generate (i) an input image palette statistically representative of pixels of an input image and (ii) a reference image palette statistically representative of pixels of a reference image, and adjusting at least some pixels of the input image to generate adjusted pixels that are statistically represented by the reference image palette. In some embodiments, a user interface for controlling the image adjustment includes a display and at least one user input device, the user interface displaying a set of colors indicative of the regions of color space represented by a palette and receiving a selection of one or more regions of the color space, so that the image adjustment adjusts those pixels of the input image lying within the one or more selected regions of the color space. | 09-17-2009 |
| 20090271433 | CLUSTERING USING NON-NEGATIVE MATRIX FACTORIZATION ON SPARSE GRAPHS - Object clustering techniques are disclosed. A nonnegative sparse similarity matrix is constructed for a set of objects. Nonnegative factorization of the nonnegative sparse similarity matrix is performed. Objects of the set of objects are allocated to clusters based on factor matrices generated by the nonnegative factorization of the nonnegative sparse similarity matrix. | 10-29-2009 |
| 20100040285 | SYSTEM AND METHOD FOR OBJECT CLASS LOCALIZATION AND SEMANTIC CLASS BASED IMAGE SEGMENTATION - An automated image processing system and method are provided for class-based segmentation of a digital image. The method includes extracting a plurality of patches of an input image. For each patch, at least one feature is extracted. The feature may be a high level feature which is derived from the application of a generative model to a representation of low level feature(s) of the patch. For each patch, and for at least one object class from a set of object classes, a relevance score for the patch, based on the at least one feature, is computed. For at least some or all of the pixels of the image, a relevance score for the at least one object class based on the patch scores is computed. An object class is assigned to each of the pixels based on the computed relevance score for the at least one object class, allowing the image to be segmented and the segments labeled, based on object class. | 02-18-2010 |
| 20100088073 | FAST ALGORITHM FOR CONVEX OPTIMIZATION WITH APPLICATION TO DENSITY ESTIMATION AND CLUSTERING - A method of maximizing a concave log-likelihood function comprises: selecting a pair of parameters from a plurality of adjustable parameters of a concave log-likelihood function; maximizing a value of the concave log-likelihood function respective to an adjustment value to generate an optimal adjustment value, wherein the value of one member of the selected pair of parameters is increased by the adjustment value and the value of the other member of the selected pair of parameters is decreased by the adjustment value; updating values of the plurality of adjustable parameters by increasing the value of the one member of the selected pair of parameters by the optimized adjustment value and decreasing the value of the other member of the selected pair of parameters by the optimized adjustment value; and repeating the selecting, maximizing, and updating for different pairs of parameters to identify optimized values of the plurality of adjustable parameters. | 04-08-2010 |
| 20100128919 | SYNCHRONIZING IMAGE SEQUENCES - As set forth herein, a computer-based method is employed to align a sequences of images. Metadata associated with images from two or more sources is received and a time stamp is extracted from the metadata. The images are sorted into sequences based at least in part upon the image source. The similarity of images from disparate sequences is measured and image pairs from disparate sequences with a similarity greater than a predetermined threshold are identified. A sequence of images is aligned by minimizing the misalignment of pairs. | 05-27-2010 |
| 20100159432 | SYSTEM AND METHOD FOR RECOMMENDING EDUCATIONAL RESOURCES - An educational recommender system and a method are provided. The method includes receiving a request to recommend a course of action related to a plurality of current students; accessing a computer database storing student data that corresponds to the plurality of current students; clustering in a computer process the plurality of current students into at least two clusters based at least on granular assessment data associated with student data corresponding to respective current students; and outputting the results of the clustering to a user. The granular assessment data includes a result of an assessment administered to respective students of the plurality of current students, and each assessment includes a plurality of questions for assessing one of the current students. The associated result includes an independent evaluation of each respective question of the plurality of questions. | 06-24-2010 |
| 20100159437 | SYSTEM AND METHOD FOR RECOMMENDING EDUCATIONAL RESOURCES - A recommender system and method is provided, including receiving a request to recommend a course of action related to a plurality of current students in accordance with a plurality of constraints and accessing a computer database storing student data that corresponds to the plurality of current students. The student data includes attribute data corresponding to respective students of the plurality of current students for describing at least one attribute related to the respective students. The method further includes clustering in a computer process the plurality of current students into a selected number of clusters based at least on sameness of attribute data corresponding to the respective current students of the plurality of current students and the plurality of constraints, and outputting the results of the clustering to a user. | 06-24-2010 |
| 20100159438 | SYSTEM AND METHOD FOR RECOMMENDING EDUCATIONAL RESOURCES - A recommender system and method including receiving a request identifying at least one current student for which a recommendation is sought and accessing stored student data including attributes associated with respective students of the current students and a plurality of predecessor students. For the predecessor students the attributes include educational resources. The method includes clustering one of predecessor students and the current students into clusters based on sameness of first selected attributes of their respective associated attributes. The method includes generating a mapping between respective students of the other of the predecessor and current students and one of the clusters based on sameness of second selected attributes associated with the students being mapped. The method then includes recommending for each of the current students the educational resource associated with the predecessor student or cluster of predecessor students that the current student is mapped with. | 06-24-2010 |
| 20100227306 | SYSTEM AND METHOD FOR RECOMMENDING EDUCATIONAL RESOURCES - An educational recommender system and a method for recommending an educational game to be used by a group of at least two students are provided. The method includes receiving a request to recommend an educational game to use with the group of students, and accessing student data relating to the at least two students including granular assessment data. The granular assessment data includes a result of at least one assessment administered to respective students, wherein each assessment includes a plurality of problems for assessing at least one of the students and the associated result includes an independent evaluation of each respective problem. The method further includes selecting an educational game that exercises the students in an academic area, including selecting the level of the academic area exercised based on granular assessment data associated with each of the respective students. | 09-09-2010 |
| 20100318477 | FAST AND EFFICIENT NONLINEAR CLASSIFIER GENERATED FROM A TRAINED LINEAR CLASSIFIER - A classifier method comprises: projecting a set of training vectors in a vector space to a comparison space defined by a set of reference vectors using a comparison function to generate a corresponding set of projected training vectors in the comparison space; training a linear classifier on the set of projected training vectors to generate a trained linear classifier operative in the comparison space; and transforming the trained linear classifier operative in the comparison space into a trained nonlinear classifier that is operative in the vector space to classify an input vector. | 12-16-2010 |
| 20110026831 | COMPACT SIGNATURE FOR UNORDERED VECTOR SETS WITH APPLICATION TO IMAGE RETRIEVAL - To compute a signature for an object comprising or represented by a set of vectors in a vector space of dimensionality D, statistics are computed that are indicative of distribution of the vectors of the set of vectors amongst a set of regions R | 02-03-2011 |
| 20110052063 | CONSISTENT HIERARCHICAL LABELING OF IMAGE AND IMAGE REGIONS - Classification of image regions comprises: recursively partitioning an image into a tree of image regions having the image as a tree root and at least one image patch in each leaf image region of the tree, the tree having nodes defined by the image regions and edges defined by pairs of nodes connected by edges of the tree; assigning unary classification potentials to nodes of the tree; assigning pairwise classification potentials to edges of the tree; and labeling the image regions of the tree of image regions based on optimizing an objective function comprising an aggregation of the unary classification potentials and the pairwise classification potentials. | 03-03-2011 |
| 20110091105 | BAGS OF VISUAL CONTEXT-DEPENDENT WORDS FOR GENERIC VISUAL CATEGORIZATION - Category context models ( | 04-21-2011 |
| 20110137898 | UNSTRUCTURED DOCUMENT CLASSIFICATION - A document classification method comprises: (i) classifying pages of an input document to generate page classifications; (ii) aggregating the page classifications to generate an input document representation, the aggregating not being based on ordering of the pages; and (iii) classifying the input document based on the input document representation. A page classifier for use in the page classifying operation (i) is trained based on pages of a set of labeled training documents having document classification labels. In some such embodiments, the pages of the set of labeled training documents are not labeled, and the page classifier training comprises: clustering pages of the set of labeled training documents to generate page clusters; and generating the page classifier based on the page clusters. | 06-09-2011 |
