Abstract: A system and method for generating groups of cluster spines for display are provided. One or more concepts for each cluster in a set of clusters are generated. Spines are formed from at least a portion of the clusters based on the concepts. At least one spine unique from all other spines is placed. One or more spine groups are generated by positioning at least one unplaced spine in relation to one of the placed unique spines. The spine groups are displayed.

Abstract: Disclosed is an automatic video summarization device and method using a fuzzy OC-SVM (one-class support vector machine) algorithm. A user's subjective decision is reflected in order to generate an effective video summary, and a method for generating flexible video summary information which satisfies the user's environment or requirements is provided. Important video segments are extracted from a given video, and a sequence of key frames is extracted from the video segments, and hence, the user can catch the contents of the video quickly and access desired video scenes.

Abstract: A spatial motion calculation apparatus includes an image position relation calculation unit that calculates first similarities based on an image position relation between an inputted groups of feature points 1 and 2, a spatial position relation calculation unit that calculates second similarities based on an spatial position relation between said inputted groups, a feature descriptor relation calculation unit that calculates third similarities based on a feature descriptor relation between said inputted groups, and a spatial motion calculation unit that estimates the spatial motion based on the result that integrates the first to third similarities.

Abstract: A method normalizes a feature of an object in an image. The feature of the object is extracted from a 2D or 3D image. The feature is displaceable within a displacement zone in the object, and wherein the feature has a location within the displacement zone. An associated description of the feature is determined. Then, the feature is displaced to a best location in the displacement zone to produce a normalized feature.

Abstract: Techniques are provided to analyze video frames of a video signal in order to distinguish regions containing a face (and body torso) from regions that contain a relatively static background. The region containing the face is referred to as a foreground region. A current video frame is divided into a plurality of elements and the foreground regions and background regions are detected. The background regions of a subsequent video frame are detected/registered using the foreground regions of the current video frame. The foreground regions of the subsequent video frame are determined using the background regions of the current video frame as a temporal reference.

Abstract: A clustering processing method for dividing a samples into a plurality of clusters based on a feature amount of each sample, the plurality of clusters each belonging to one of a plurality of layers composed of M layers (M=2, . . . , K), the clustering processing method comprises a sample allocating step of allocating a sample targeted for processing to a cluster belonging to a first layer, based on a result of comparing the feature amount of the target sample with a representative feature amount of each of clusters belonging to the first layer; a determination step of determining whether to allocate a cluster belonging to an M?1th layer to an Mth layer; and a cluster allocating step of allocating a cluster belonging to the M?1th layer to the Mth layer, if it is determined in the determination step to allocate a cluster belonging to the M?1th layer to the Mth layer.

Abstract: Methods and systems for automated annotation of persons in video content are disclosed. In one embodiment, a method of identifying faces in a video includes the stages of: generating face tracks from input video streams; selecting key face images for each face track; clustering the face tracks to generate face clusters; creating face models from the face clusters; and correlating face models with a face model database. In another embodiment, a system for identifying faces in a video includes a face model database having face entries with face models and corresponding names, and a video face identifier module. In yet another embodiment, the system for identifying faces in a video can also have a face model generator.

Abstract: A method for facilitating semantic event classification of a group of image records related to an event. The method using an event detector system for providing: extracting a plurality of visual features from each of the image records; wherein the visual features include segmenting an image record into a number of regions, in which the visual features are extracted; generating a plurality of concept scores for each of the image records using the visual features, wherein each concept score corresponds to a visual concept and each concept score is indicative of a probability that the image record includes the visual concept; generating a feature vector corresponding to the event based on the concept scores of the image records; and supplying the feature vector to an event classifier that identifies at least one semantic event classifier that corresponds to the event.

Abstract: This invention relates to supervised or unsupervised classification of biological datasets. Specifically, the invention relates to the use of Graph Embedding as a method of reducing dimensionality thereby improving supervised classification of classes, both conventional and new ones.

Abstract: An image evaluation apparatus is provided, which calculates a characteristic value indicating a state of appearance of objects corresponding to person a and person b appearing in image A and an object corresponding to person b appearing in image B. Subsequently, the image evaluation apparatus specifies person b? as the photographer of image B and calculates a likelihood degree indicating accuracy of the determination. Further, the image evaluation apparatus calculates an importance degree of each of images A and B according to the characteristic values of person a and person b appearing in image A and image B and the likelihood degree of the photographer of image B.

Abstract: There is provided a printing system including a reading unit that reads paper identification information of a paper sheet, a first controller that implements control for, when instructed to print document data, causing the reading unit to read the paper identification information of the paper sheet used for printing and transmitting a request for a document containing the read paper identification information, and a second controller that implements control for, when printing document data containing the paper identification information received in response to the request for the document on the paper sheet, causing the reading unit to read the paper identification information of the paper sheet used for printing and, if the read paper identification information and the received paper identification information contained in the document data do not match, inhibiting printing of the document data.

Abstract: Described herein are a system and a method for abnormal behavior detection using automatic classification of multiple features. Features from various sources, including those extracted from camera input through digital image analysis, are used as input to machine learning algorithms. These algorithms group the features and produce models of normal and abnormal behaviors. Outlying behaviors, such as those identified by their lower frequency, are deemed abnormal. Human supervision may optionally be employed to ensure the accuracy of the models. Once created, these models can be used to automatically classify features as normal or abnormal. This invention is suitable for use in the automatic detection of abnormal traffic behavior such as running of red lights, driving in the wrong lane, or driving against traffic regulations.

Abstract: The present invention provides systems and methods to automatically analyze Landsat satellite data of forests. The present invention can easily be used to monitor any type of forest disturbance such as from selective logging, agriculture, cattle ranching, natural hazards (fire, wind events, storms), etc. The present invention provides a large-scale, high-resolution, automated remote sensing analysis of such disturbances.

Abstract: An interactive photo annotation method uses clustering based on facial similarities to improve annotation experience. The method uses a face recognition algorithm to extract facial features of a photo album and cluster the photos into multiple face groups based on facial similarity. The method annotates a face group collectively using annotations, such as name identifiers, in one operation. The method further allows merging and splitting of face groups. Special graphical user interfaces, such as displays in a group view area and a thumbnail area and drag-and-drop features, are used to further improve the annotation experience.

Abstract: This invention relates to rearranging a cluster map of voxels in an image aiming at the reduction of sub-cluster scatter. The cluster map that includes two or more cluster levels is displayed to the user along with the distribution of the voxels within each respective cluster levels. The aim is to enable the user to evaluate the quality of the cluster map and based on the evaluation to change the distribution of the voxels. Such a change in the distribution will result in an update of the cluster map.

Abstract: Disclosed herein is a content management apparatus, including: content inputting means for inputting a content with which position information is associated; position information acquisition means for acquiring the position information associated with the content inputted by the content inputting means; tree production means for producing binary tree structure data corresponding to a binary tree having leaves to which contents inputted by the content inputting means correspond based on the position information of the contents acquired by the position information acquisition means; and determination means for extracting a node which satisfies a predetermined condition from among nodes of the binary tree structure data produced by the tree production means and determining those of the contents which belong to the extracted node as one group.

Abstract: A method for measuring multimedia communication quality is disclosed. The multimedia video communication quality may be objectively reflected through the embedment and extraction of digital watermark under a precondition that the quality of the multimedia video data is not obviously affected. In the invention, each frame of the multimedia video data is uniformly divided into blocks of equal size and watermark data is embedded in each of the blocks, so that the watermark may be uniformly distributed. The multimedia video data are divided into groups, and the watermark is embedded in a part of the frames with equal interval between the frames in each group to reduce the effect of the watermark on the data. The watermark information is directly embedded in the spatial domain of the original video data.

Abstract: A feature vector is encoded into a sparse binary vector. The feature vector is retrieved, for example from storage or a feature vector generator. The feature vector represents a media object or other data object. One or more permutations are generated, the dimensionality of the generated permutations equivalent to the dimensionality of the feature vector. The permutations may be generated randomly or formulaically. The feature vector is permuted with the one or more permutations, creating one or more permuted feature vectors. The permuted feature vectors are truncated according to a selected window size. The indexes representing the maximum values of the permuted feature vectors are identified and encoded using one-hot encoding, producing one or more sparse binary vectors. The sparse binary vectors may be concatenated into a single sparse binary vector and stored. The sparse binary vector may be used in the similarity search, indexing or categorization of media objects.

Abstract: A similar image retrieving device (1) comprises: an image database (21) for storage of sets of image data, and sets of keywords each associated with a corresponding image data; a cluster classification section (11) to read the sets of image data, provide a respective one of the sets of image data with a compatibility value as an index representative of a set of compatibilities of a corresponding one of the sets of keywords, and classify the sets of image data into clusters thereof in accordance with the compatibility value; an optimum cluster extracting section (12) to provide the set of query image data with a compatibility value, and select one of clusters to which the query image data is to belong to minimize an error caused in a Projection onto Convex Sets using the clusters; and a similar image extracting section (13) to output, as a similar image, a set of image data provided a close compatibility value, among the sets of image data belonging to the cluster selected by the optimum cluster extractor.

Abstract: An image classification device includes a characteristic value set calculation unit 11 that calculates a characteristic value set of the whole image for each of multiple sets of image data in an image database 51, detects an edge of the set of the image data, and calculates a characteristic value set of the detected edge portions; a first clustering unit 12 that classifies the multiple sets of image data into multiple clusters on the basis of the characteristic value sets of the whole images; a second clustering unit 13 that further classifies the multiple clusters classified by the first clustering unit 12 into multiple clusters on the basis of the characteristic value sets of the edge portions; and a cluster integration unit 14 that determines which pixels constitutes a subject in each of the multiple sets of image data, based on the composition of the image, and integrates some of the multiple clusters classified by the second clustering unit 13 together based on the pixels constituting the subject.

Abstract: The present invention relates to a volume recognition method comprising the steps of: a) capturing three-dimensional image data using a 3D imaging system 3, wherein said image data represent a plurality of points 5, each point 5 having at least a set of coordinates in a three-dimensional space; b) grouping at least some of the points 5 in a set of clusters 6; c) selecting, according to a first set of parameters such as position and size, a cluster 6 corresponding to an object of interest 1 located in range of said imaging system 3; d) grouping at least some of the points 5 of the selected cluster 6 in a set of sub-clusters according to a second set of parameters comprising their positions in the three-dimensional space, wherein each sub-cluster has a centroid 11 in the three-dimensional space; and e) associating a volume 12 to each of at least some of said sub-clusters, wherein said volume 12 is fixed to the centroid 11 of said sub-cluster.

Abstract: There is disclosed a label image editing apparatus for editing a label image on a recording media having a data side on which data is recorded, and a label side on which a label image is plotted to visually confirm recording contents on the data side. The label image editing apparatus comprises: a data analyzing section that analyzes data to be recorded on the recording media and/or data to be reproduced from the recording media; and a layout display section that displays, as a layout of the label image, a layout according to an analyzing result by the data analyzing section.

Abstract: Systems, methods and computer program products on storage devices for shape clustering and applications in processing various documents, including an output of an optical character recognition (OCR) process. The output of an OCR process is classified into a plurality of clusters of clip images and a representative image for each cluster is generated to identify clusters whose clip images were incorrectly assigned character codes by the OCR process.

Abstract: 3D models of the engineering class usually have a large number of connected components, with small numbers of large triangles, often with arbitrary connectivity. To enable compact storage and fast transmission of large 3D mesh models, an efficient compression strategy specially designed for 3D mesh models is provide. A method for encoding a 3D mesh model comprises determining and clustering repeating components, normalizing the components, wherein scaling factors are clustered and orientation axes are clustered, encoding the connected components using references to the clusters, and entropy encoding the connected components.

Abstract: A method for creating an image album includes selecting a subset of images from a source set and creating a plurality of image albums by arranging the subset of images over one or more pages. Each image album is evaluated by a penalty detection unit (215) to generate a penalty score which is a measure of the aesthetic quality of an image album. One or more of the image albums having the lowest penalty scores are presented to the user. A system for arranging a number of images into an image album is also provided.

Abstract: A dice recognition system and a dice recognition method for uncontrolled environments are provided. In the present invention, the number of dot on a dice is automatically recognized in an uncontrolled environment by using multiple cameras. The present dice recognition system is different in at least two aspects from any existing automatic dice recognition system which uses a single camera for recognizing dice in an enclosed environment. Firstly, an existing automatic dice recognition system uses a single camera to obtain planar images for dice recognition, while the present dice recognition system uses multiple cameras to obtain different viewpoints images for dice recognition. Secondly, the present dice recognition system is designed for uncontrolled environments, and which can be applied to an open-table game in a general gambling place for dice recognition without changing the original dice, dice cup, and other related objects.

Abstract: Systems, methods, and computer program products on storage devices for shape clustering and applications in processing various documents, including an output of an optical character recognition (OCR) process. The output of an OCR process is classified into a plurality of clusters of clip images and a representative image for each cluster is generated to identify clusters whose clip images were incorrectly assigned character codes by the OCR process.

Abstract: An object detection and classification method and apparatus, the method includes: inputting an image; performing window scan on the image to make, for each class, object existence decision on each window, and making, on a window of which the decision is positive, an object class decision to obtain an object classification confidence of the window; performing, for all classes, spatial neighborhood merging on all windows with positive result of object existence decision to obtain merged regions and object detection confidences thereof; judging, for each merged region, whether the object detection confidence of the merged region is higher than a predetermined threshold; calculating, for each class, if higher than the predetermined threshold, a merged object classification confidence for all the windows with positive result of object existence decision within the merged region; and determining a class with a highest merged object classification confidence as the class of the merged region.

Abstract: A clustering procedure for grouping a set of images is selected from amongst plural clustering procedures. A predetermined categorization of objects such as images is input, and image features are extracted from each image in the set of images. A comparison measure is determined, by which to compare respective features of the set of images. Respective features between the images in the set of images are compared, based on the comparison measure, and a group of measures representing the differences between features of respective images is output. The plural clustering procedures are applied to the set of images to cluster the images based in part on the calculated group of measures. A clustering quality score is generated for each clustering procedure, based on the clusters created by the clustering procedure and the predetermined categorization of images. The clustering procedure with a high clustering quality score is selected.

Abstract: A system and method for displaying groups of cluster spines is provided. Groups of cluster spines are obtained. Each group includes one or more spines with one or more clusters each associated with at least one concept. Group concept score vectors are generated for each of the spine groups by aggregating the concepts for that spine group. The group concept score vectors for the spine groups are compared and those spine groups that are unique are identified. The unique spine groups are placed into a display by arranging the unique spine groups at equal distance angles around a center ring provided in the display.

Abstract: A method of selecting at least one representative image from a plurality of images, the method comprising the steps of: dividing (201) the plurality of images into clusters according to a predetermined characteristic of the content of the plurality of images; selecting (203) at least one of the clusters based on the number of images in each of the clusters; and selecting (205) at least one image from the selected at least one cluster as the representative image.

Abstract: According to one embodiment, an electronic apparatus extracts face images of persons from video content data and outputs timestamp information indicating time points at which each extracted face image appears in the video content data, and displays face images in each column of a plurality of face image display areas arranged in a matrix based on the time stamp information. The apparatus detects presence or absence of a face area in each frame consisting of the video content data and decides a cutout range of the detected face area. And, the apparatus adjusts a case in which the cutout range of the decided face area protrudes outside the frame.

Abstract: A method of grouping images captured in a common location, including receiving a collection of images; classifying the images into a set of events, where each image in the collection belongs to no more than one event; analyzing background region(s) of images from each event to determine one or more features that represent the event; and comparing features from at least two events to determine which events occurred in a common location.

Abstract: Embodiments of computer implemented methods and systems for object clustering and identification are described. One example embodiment includes receiving an unclustered video object, determining a first distance between the unclustered video object and an arbitrary representative video object, the arbitrary representative video object being selected from representative video objects, estimating distances between the unclustered video object and the representative video objects based on the first distance and precalculated distances between the arbitrary representative video object and the representative video objects, and, based on the estimated distances, selectively associating the unclustered video object with a video cluster, thereby producing a clustered video object.

Abstract: A document recognition system and method, where images are represented as a collection of primitive features whose spatial relations are represented as a graph. Useful subsets of all the possible subgraphs representing different portions of images are represented over a corpus of many images. The data structure is a lattice of subgraphs, and algorithms are provided means to build and use the graph lattice efficiently and effectively.

Abstract: An image processing method comprises: clustering images of a set of images to generate a plurality of scenes each comprising an unordered cluster of images; ordering images within scenes respective to video coherence to generate ordered scenes comprising ordered sequences of images; and generating video content as images ordered in accordance with the ordered sequences of images comprising the scenes. In some embodiments, the video content is converted to video comprising video frames played at a predetermined frame rate.

Abstract: Techniques for shape clustering and applications in processing various documents, including an output of an optical character recognition (OCR) process. The output of an OCR process is classified into a plurality of clusters of clip images and a representative image for each cluster is generated to identify clusters whose clip images were incorrectly assigned character codes by the OCR process.

Abstract: Machine-readable media, methods, apparatus and system for obtaining and processing image features are described. In some embodiments, groups of training features derived from regions of training images may be trained to obtain a plurality of classifiers, each classifier corresponding to each group of training features. The plurality of classifiers may be used to classify groups of validation features derived from regions of validation images to obtain a plurality of weights, wherein each weight corresponds to each region of the validation images and indicates how important the each region of the validation images is. Then, a weight may be discarded from the plurality of weights based upon a certain criterion.

Abstract: An interest point detection technique is presented. More particularly, for each of possibly multiple image pyramid resolutions, a cornerness image is generated. One or more potential interest point locations are identified in the cornerness image. This involves finding locations associated with a pixel that exhibits a higher corner strength value than pixels in a prescribed-sized surrounding pixel neighborhood. The potential interest point locations are then clustered to identify groups that likely derive from a same 2D structure. Potential interest point locations in one or more of the identified groups are respectively combined to produce a single location that represents the combined group. The representative location of each group having one is then designated as an interest point. An optional location refinement can also be implemented.

Abstract: A method of browsing face regions in digital images in a photo displaying system includes detecting a plurality of face regions from a plurality of images, grouping the face regions into a plurality of clusters based on similarities of the face regions, determining a degree of connection between the clusters, modifying the degree of connection between the clusters according to a relationship of the face regions, and displaying the face regions according to the degree of connection between the clusters.

Abstract: A system and method for verifying the face of a user using a light mask are provided. The system includes a facial feature extraction unit for extracting a facial feature vector from a facial image received from a camera. A non-user Gaussian Mixture Model (GMM) configuration unit generates a non-user GMM from a facial image stored in a non-user database (DB). A user GMM configuration unit generates a user GMM by applying light masks to a facial image stored in a user DB. A log-likelihood value calculation unit inputs the facial feature vector both to the non-user GMM and to the user GMM, thus calculating log-likelihood values. A user verification unit compares the calculated log-likelihood values with a predetermined threshold, thus verifying whether the received facial image is a facial image of the user.

Abstract: An action analysis apparatus includes an acquiring unit that acquires moving image data including a series of frame image data obtained by imaging a human body, a unit that detects at least one image area in which a predetermined portion of the imaged human body is imaged in the frame image data included in the acquired moving image data and generates and stores information to identify the detected image area, and a unit that generates at least one of feature quantity information about an action of the predetermined portion of the human body detected in the frame image data and generates and stores information to identify frame image data at a timing at which the feature quantity information satisfies a predetermined condition as feature time point information. The feature time point information is applied to present the moving image data to a user.

Abstract: Described is a system for anomaly detection to detect an anomalous object in an image, such as a concealed object beneath a person's clothing. The system is configured to generate a subspace model for a normal class using training images. The normal class represents normal objects in a common class. The system receives a novel image having an object in the common class. A set of geometric landmarks are identified in the object in the novel image for use in registering the image. The novel image is registered by warping the image so that the geometric landmarks coincide in the novel image and the training images, resulting in a warped novel image having an object. Thereafter, the system determines if the object in the warped novel image is anomalous by measuring the distance of the warped novel image from the subspace model. Finally, if anomalous, an operator is notified accordingly.

Abstract: When images are classified into categories, which of the categories has important images can be understood easily without a burned on a user. For this purpose, a category weight calculation unit statistically calculates a weight of each of the categories obtained by classification of the images, based on at least one of characteristic quantities comprising the number of images therein found by considering similar images therein, a total photography time thereof, a rate of similar images therein, a rate of human images therein, and an average number of human faces therein.

Abstract: Properties of pixels of a digital image are sampled within different subdivisions of an editing tool impression to produce different pixel property distributions. The property distributions from each region may be automatically classified to identify different edit classes within the property space, which are then used to apply an edit effect to the digital image within the tool impression. The edit classes are represented by an edit profile, the generation of which may be completely automated based on selection of a tool impression, or partially automated using the selection of the tool impression and receipt of classification guidance input, such as one or more parameters received from user input or a configuration file. The edit classes may also be generated without reference to the pixel property distributions, such as via user input.

Abstract: Systems, methods and computer program products for shape clustering and applications in processing various documents, including an output of an optical character recognition (OCR) process. Clip images defined in a received OCR output are classified into a plurality of clusters of clip images. Clip images in each of the plurality of clusters are processed to generate a cluster image for each cluster. Shape differences between the cluster images of a first cluster and a second cluster and between the cluster images of the first cluster and a third cluster are used to determine a level of confidence in one or more first OCR character codes assigned to the first cluster.

Abstract: A method includes receiving one or more query images and identifying multiple features associated with an object or an activity using the one or more query images. The method also includes accessing a sparse representation index using the identified features. The sparse representation index includes a multi-dimensional polytope having multiple vertices, and the features identify a point in the polytope. The method further includes identifying multiple vertices in the sparse representation index that are associated with the identified point and providing one or more images associated with the identified vertices. In addition, the method includes identifying one or more clusters of features associated with the identified vertices and providing one or more additional images associated with the one or more identified clusters. The one or more clusters may be identified using a clustering index identifying the clusters and features of training images associated with the clusters.

Abstract: System and method for mapping a location of each of a plurality of devices in a data center. In one embodiment, the method comprises receiving image data comprising an image of at least a portion of the data center from a source; processing the image data to locate visual identifiers displayed in the image, wherein each of the visual identifiers is associated with one of the devices or with a spatial reference point; extracting the located visual identifiers and determining spatial coordinates for each of the identified visual identifiers from the image; and determining the spatial reference points from the image.

Abstract: A process for the automatic recognition of abnormalities in anatomical structures is described together with a processing system and a computer program for implementing the aforesaid process, comprising the operations of: acquiring (10) a plurality of two-dimensional images of at least one portion of a patient's body capable of forming a three-dimensional representation of at least one anatomical structure under observation, segmenting (20) a region of interest in the said three-dimensional representation which potentially contains anomalies, selecting (30, 40) volume image elements (voxels) from the segmented region which are likely to form a part of abnormalities in the anatomical structure represented, on the basis of predetermined morphological parameters, agglomerating (60) the said voxels into analysis units on the basis of the distribution of the spatial density of the voxels selected, and classifying (70) the said analysis units as elements suspected of being parts of abnormalities or as elements w

Abstract: Techniques for shape clustering and applications in processing various documents, including an output of an optical character recognition (OCR) process. The output of an OCR process is classified into a plurality of clusters of clip images and a representative image for each cluster is generated to identify clusters whose clip images were incorrectly assigned character codes by the OCR process.