Abstract: Methods and systems for measuring group behavior are provided. Group behavior of different groups may be measured objectively and automatically in different environments including a dark environment. A uniform visible signal comprising images of members of a group may be obtained. Facial motion and body motions of each member may be detected and analyzed from the signal. Group behavior may be measured by aggregating facial motions and body motions of all members of the group. A facial motion such as a smile may be detected by using the Fourier Lucas-Kanade (FLK) algorithm to register and track faces of each member of a group. A flow-profile for each member of the group is generated. Group behavior may be further analyzed to determine a correlation of the group behavior and the content of the stimulus. A prediction of the general public's response to the stimulus based on the analysis of the group behavior is also provided.

Abstract: A method and system for comparing measurements of a device under test (DUT) to measurements taken of similar equipment are provided. The method includes communicatively connecting a mobile computing device to one or more measurement devices, and receiving measurement data from the one or more measurement devices. The mobile computing device determines an equipment identifier of the DUT, and retrieves information associated with the equipment, which may include previous measurements of other devices or reference documents. The mobile computing device presents the retrieved information along with the received measurement data for comparison.

Abstract: The invention described herein is generally directed to methods for analyzing an image. In particular, crowded field images may be analyzed for unidentified, unobserved objects based on an iterative analysis of modified images including artificial objects or removed real objects. The results can provide an estimate of the completeness of analysis of the image, an estimate of the number of objects that are unobserved in the image, and an assessment of the quality of other similar images.

Abstract: A method for selecting important digital images in a collection of digital images, comprising: analyzing the digital images in the collection of digital images to identify one or more sets of similar digital images; identifying one or more sets of similar digital images having the largest number of similar digital images; selecting one or more digital images from the identified largest sets of similar digital images to be important digital images; and storing an indication of the selected important digital image in a processor accessible memory.

Abstract: In embodiments of optical flow accounting for image haze, digital images may include objects that are at least partially obscured by a haze that is visible in the digital images, and an estimate of light that is contributed by the haze in the digital images can be determined The haze can be cleared from the digital images based on the estimate of the light that is contributed by the haze, and clearer digital images can be generated. An optical flow between the clearer digital images can then be computed, and the clearer digital images refined based on the optical flow to further clear the haze from the images in an iterative process to improve visibility of the objects in the digital images.

Abstract: An image processing apparatus comprises a registration unit configured to perform a first registration between a first set of image data and a second set of data, and a second registration between the first set of image data and the second set of data. The apparatus also comprises a registrability determination unit configured to determine a difference between the first registration and the second registration, and to determine a measure of registrability between the first set of image data and the second set of data based on the difference between the first registration and the second registration.

Abstract: A system and method classify a test image. At least one processor receives a data graph computed from the test image. Further, a graph lattice is received. The graph lattice includes a plurality of nodes, each including a subgraph, a weight and at least one mapping of the subgraph to data graphs of a plurality of training images. The training images correspond to a plurality of classes. The data graph of the test image is mapped by the subgraphs of the nodes. Mappings between the graph lattice and the data graphs of the training images are compared with mappings between the graph lattice and the data graph of the test image to determine weighted votes of similarity between the data graphs of the training images and the data graph of the test image. The class of the test image is determined from the weighted votes.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for creating an image similarity model. In one aspect, a method includes obtaining feature vectors for images in a set of images, and determining first similarity measures for unlabeled images relative to a reference image. The first similarity measures are independent of first similarity feedback between the unlabeled images and the reference image. The unlabeled images are ranked based on the first similarity measures, and a weighted feature vector is generated based, in part, on the ranking. Second similarity measures are determined, independent of second similarity feedback, for labeled images and a second reference image. The labeled images are ranked based on the second similarity measures. The weighted feature vector is adjusted based, in part, on a comparison of the ranking to a second ranking of the labeled images that is based on the second similarity feedback.

Abstract: An apparatus is configured to show telestration in 3-D to a surgeon in real time. A proctor is shown one side of a stereo image pair, such that the proctor can draw a telestration line on the one side with an input device. Points of interest are identified for matching to the other side of the stereo image pair. In response to the identified points of interest, regions and features are identified and used to match the points of interest to the other side. Regions can be used to match the points of interest. Features of the first image can be matched to the second image and used to match the points of interest to the second image, for example when the confidence scores for the regions are below a threshold value. Constraints can be used to evaluate the matched points of interest, for example by excluding bad points.

Abstract: A system may recognize faces within an image by using wireless identifiers captured at the time the image was taken to determine a list of candidates for facial recognition. A database may contain people associated with one or more wireless identifiers, which may be identifiers associated with various protocols, such as Bluetooth, cellular telephones, WiFi, or other protocols. In some cases, the list of candidates may be expanded by using candidate's social networks. The recognized faces may be tagged in the image as metadata, then used in various scenarios. In one scenario, an album of images from an event may be created by matching people who were tagged in images. In another scenario, people may exchange business contact information or social network contacts by taking images of each other.

Abstract: An apparatus and a method for refining a value of a similarity measure are described. A similarity measure is assigned to a pixel or a group of pixels of a disparity map, which is assigned to at least two stereo images each having a plurality of pixels. The similarity measure constitutes an estimate for a match quality of the pixel or the group of pixels. For refinement of the value of the similarity measure, the similarity measure between a pixel or a group of pixels in a first stereo image and a corresponding pixel or a group of corresponding pixels in a second stereo image is determined. A contrast value for the pixel or the group of pixels of the first or the second stereo image is determined and the value of the similarity measure is corrected by a correction value that is a function of the determined contrast value.

Abstract: Indexing regions of changed pixels (ROCHs) in a collection of images by receiving a collection of images. Estimate and/or validate a background among the collection of images. Detect the changes between images in the collection. Associate the detected changes between the images and classifying the associated changes. This image processing method and system may be used for image indexing and object classification.

Abstract: A hardware-implemented function evaluator performs mathematical calculations at high speeds to generate data values in place of an LUT. The disclosed embodiments can generate a small number of output values from a large number of input values. The calculations can use functions that are monotonically increasing such as, for example, square root, power curves, and trigonometric functions.

Abstract: According to an embodiment, an information processing system includes a determination unit, a selection unit, and a display control unit. The determination unit is configured to determine whether a first feature value extracted from a first image and a second feature value extracted from a second image are identical or similar. The selection unit is configured to select content data from a plurality of content data so that the selected content data is different between when it is determined that the first feature value and the second feature value are identical or similar and when it is determined that the first feature value and the second feature value are not identical or similar. The display control unit is configured to display the selected content data on a display unit.

Abstract: One exemplary embodiment involves receiving a test image generating, by a plurality of maps for the test image based on a plurality of object images. Each of the object images comprises an object of a same object type, e.g., each comprising a different face. Each of the plurality of maps is generated to provide information about the similarity of at least a portion of a respective object image to each of a plurality of portions of the test image. The exemplary embodiment further comprises detecting a test image object within the test image based at least in part on the plurality of maps.

Abstract: The pattern inspection apparatus of the present invention performs comparison between images of regions corresponding to patterns formed to be same patterns, thereby determining mismatch portions across the images to be defects. The apparatus includes multiple sensors that synchronously acquire images of shiftable multiple detection systems different from one another, and an image comparator section corresponding thereto. In addition, the apparatus includes a means for detecting a statistical offset value from the feature amount to be a defect, thereby properly detecting the defect even when a brightness difference is occurring in association with film a thickness difference in a wafer.

Abstract: From a sample image, a fertilization test method determines the ratio of fertilized cells in the image by identifying cells in the image and calculating cell properties for each cell. An area is determined between a cell body and an outer search limit to search for a fertilization membrane. A cell outline is defined for each cell and cell membrane edges are found within the search area by changing the cell outline size between the cell body boundary the outer search limit, checking for a match with detected cell membrane edges. A cell is determined to be fertilized based on matches between detected cell membrane edges and the cell outline, patterns of contrast changes indicated by a cell membrane, or circles fit to cell membrane edges.

Abstract: An apparatus for estimating a disparity map based on at least two images is provided. The apparatus includes at least two processing units, which include a pixel recursion unit configured to determine a disparity value as a pixel recursion disparity candidate based on a plurality of pixel values of the at least two images and a selector configured to select a selected disparity candidate to determine at least one of the disparity map values of the disparity map. The selector is adapted to select the selected disparity candidate from a candidate group assigned to the selector. The candidate group assigned to the selector includes the pixel recursion disparity candidate, a second disparity candidate and a third disparity candidate. Moreover, the selector is adapted to select the selected disparity candidate independently from a different selector of a different processing unit of the at least two processing units.

Abstract: A method for determining that a user associated with a first identifiable device or identifiable service is also associated with a second identifiable device or identifiable service by a) generating one or more first image descriptors for one or more first images stored on the first identifiable service associated with a first user, b) generating one or more second image descriptors for one or more second images stored on the second identifiable service associated with a second user, c) calculating, based on the generated first and second image descriptors, the probability that the first user is also the second user. Also provided is a computer readable storage medium containing program code for implementing the method.

Abstract: Systems and related methods for detecting a scene in video content are provided. In one example, a scene detection program identifies a plurality of shots in the video content and selects a target shot. The program builds a forward window including the target shot and having shots that are temporally ahead of the target shot, and a rearward window having shots that are temporally behind the target shot. For each of the shots in the forward window the program determines a dissimilarity between a selected shot in forward window and each of the other shots in the rearward window. If one or more of the dissimilarities is less than a scene boundary threshold, the program determines that the scene does not begin at the target shot. If none of the dissimilarities is less than the scene boundary threshold, the program determines that the scene begins at the target shot.

Abstract: An image processing device includes an in-plane pattern detector that selects a pixel of interest in a frame image of interest, calculates in-plane correlation index values representing correlations between the pixel of interest and in-plane pixel patterns including the pixel of interest, and selects a most highly correlated pattern as an in-plane addition pattern. A reference pattern detector calculates inter-plane correlation index values representing correlations between the in-plane pixel addition pattern and reference pixel patterns in a reference frame image temporally adjoining the frame of interest, and selects a most highly correlated reference pixel pattern. A pixel adder adds the values of the pixels in the selected in-plane pixel pattern and the selected reference pixel addition pattern to generate a corrected pixel value, thereby achieving high sensitivity and a high signal-to-noise ratio under low illumination, with little loss of resolution.

Abstract: Embodiments of the invention provide methods, devices, and systems for personalizing presentation instruments. According to one embodiment, a method for personalizing presentation instruments may include providing account information for a plurality of accounts and providing a plurality of images. Each of the images may be associated with an account and may be formatted according to one or more defined parameters to facilitate placement of each image onto a presentation instrument. Each formatted image may be overlaid or placed onto a presentation instrument to personalize each presentation instrument and each presentation instrument may be associated with account information corresponding to the image overlaid or placed on the presentation instrument.

Abstract: A system and method for retrieving contact information based on image recognition searches is disclosed. A requestor takes a picture of a user or retrieves a storage image of a user and transmits the image to an image recognition module. The image recognition module identifies the user and determines whether the requestor can receive access to the user's contact information based on permission rules. For example, the permission rule includes a requirement that the user and the requestor be sufficiently related on a social graph generated by a social network application. The permission rules can also include a requirement that the requestor have a predetermined proximity to the image. Once the permission rules are satisfied, the image recognition module transmits the user's contact information to the requestor.

Abstract: Light detection and ranging (LIDAR) imaging systems, method, and computer readable media for generating super-resolved images are described. Super-resolved images are generated by obtaining data sets of cloud points representing multiple views of an object where the views have a view shift, enhancing the views by duplicating cloud points within each of the data sets, compensating for the view shift using the enhanced views, identifying valid cloud points, and generating a super-resolved image of the object by integrating valid cloud points within the compensated, enhanced views.

Abstract: A method for determining a matching score between a first set of n1 feature points, and a second set of n2 feature points includes producing a triple-wise affinity tensor, determining a leading eigenvector of the triple-wise affinity tensor, iteratively producing a binary optimal assignment vector and determining a matching score between the first set of feature points and the second set of feature points. The triple-wise affinity tensor includes the affinity score of assignments of triplets of feature points of the first set of feature points and triplets of feature points of the second set of feature points. The procedure of iteratively producing a binary optimal assignment vector is performed by discretization of the leading eigenvector. The procedure of determining a matching score is performed according to the triple-wise affinity tensor and according to the optimal assignment vector.

Abstract: A method, a system, and a program for high-fidelity three-dimensional modeling of a large-scale urban environment, performing the following steps: acquiring imagery of the urban environment, containing vertical aerial stereo-pairs, oblique aerial images; street-level imagery; and terrestrial laser scans, acquiring metadata pertaining to performance, spatial location and orientation of imaging sensors providing the imagery; identifying pixels representing ground control-points and tie-points in every instance of the imagery where the ground control-points and tie-points have been captured; co-registering the instances of the imagery using the ground control-points, the tie-points and the metadata, and referencing the co-registered imagery to a common, standard coordinate system.

Abstract: Provided are an age estimation apparatus, an age estimation method, and an age estimation program capable of reducing the labor of labeling the image data used for age estimation. An age estimation apparatus for estimating an age of a person on image data includes a dimension compression unit for applying dimension compression to the image data to output low dimensional data; a clustering unit for performing clustering of the low dimensional data outputted; a labeling unit for labeling representative data of each cluster among the low dimensional data clustered; and an identification unit for estimating an age of a person on the basis of a learning result using a feature amount contained in labeled low dimensional data and unlabeled low dimensional data.

Abstract: A method for locating an electronic apparatus, the method includes identifying a mobile communication device that is proximate the electronic apparatus; receiving location information embedded in an image file by the mobile communication device and transferred from the mobile communication device; and storing the location information in the electronic apparatus.

Abstract: A system and a method for playing a photograph-based game are provided. The method includes establishing a communication link between a game playing system and one or more game playing devices, each of which is operated by a respective player. Game rules are presented to the player(s) on the respective game playing device(s). The game rules include at least one task for the submission of at least one photographic image. Provision is made for receiving a photographic image in the game playing system which has been submitted via the established link from the game playing device in response to the presented task. An image signature is computed for the submitted photographic image based on visual features extracted from the image and a relevance to the task is computed, based on the computed image signature. A score for the game is output for each player, based on the computed relevance of the submitted images for each of the tasks.

Abstract: Determining correspondence between image regions includes identifying first and second regions of visual content including pixels in a computer system. The first region includes a first patch of pixels having a first mapping to a second patch of pixels in the second region. Iterative evaluations of the first and second regions are performed, each including at least (i) a first evaluation phase selecting a best mapping for the first patch, according to a distance metric, the best mapping selected from among the first mapping and a second mapping obtained from mappings of nearby pixels, and (ii) a second evaluation phase selecting one of the best mapping and a third mapping obtained by perturbing the second mapping. A result of the iterative evaluations is recorded in the computer system that indicates a third patch of pixels in the second region identified in the iterative evaluations.

Abstract: Establishments are identified in geo-tagged images. According to one aspect, text regions are located in a geo-tagged image and text strings in the text regions are recognized using Optical Character Recognition (OCR) techniques. Text phrases are extracted from information associated with establishments known to be near the geographic location specified in the geo-tag of the image. The text strings recognized in the image are compared with the phrases for the establishments for approximate matches, and an establishment is selected as the establishment in the image based on the approximate matches. According to another aspect, text strings recognized in a collection of geo-tagged images are compared with phrases for establishments in the geographic area identified by the geo-tags to generate scores for image-establishment pairs. Establishments in each of the large collection of images as well as representative images showing each establishment are identified using the scores.

Abstract: A store system includes a reading unit that includes an image acquiring unit and an image output unit, and a sales registration apparatus that includes a similar image detection unit and a sales registration unit. The image acquiring unit acquires an image that is captured by an image capturing unit. The image output unit outputs the acquired image. The similar image detection unit detects an image of a product that is similar to at least a portion of the output image by referencing product management information in which information relating to sales registration of a product and an image of the product are associated for each product. The sales registration unit registers sales of a product based on information relating to the sales registration associated with the image of the detected product.

Abstract: Systems and methods for measuring consistency between two objects based upon a rank of object elements instead of based upon the values of those object elements. Objects being compared can be represented by d-dimension feature vectors, U and V, where each dimension includes an associated value. U and V can be converted to rank vectors, P and Q, where values of U and V dimensions are replaced by an ordered rank or a function thereof. Analysis directed to the consistency between U and V can be accomplished by determining consistency between P and Q, which can be more efficient and more accurate, particularly with regard to illumination-invariant comparisons.

Abstract: An image processing apparatus includes an image acquisition unit that acquires a first image and a second image each of which includes a character string, an extraction unit that extracts feature points included in each of the first image and the second image, a setting unit that sets partial regions including characters which are continuously arranged in an arrangement direction of the character string in each of the first image and the second image, and a specification unit that compares positions of the feature points included in the partial regions set in the first image with positions of the feature points included in the partial regions set in the second image so as to specify the partial regions set in the second image corresponding to the partial regions set in the first image, and specifies corresponding points in each of the specified partial regions.

Abstract: Systems, methods, and computer storage mediums are provided for matching multiple photographs together. An example method includes receiving a first collection of photographic images. The photographic images in the first collection are clustered into one or more composite sets of photographic images based on a comparison of the metadata associated with each photographic image in the first collection meeting a predetermined similarity threshold. An image overlap is determined between each photographic image within each of the one or composite sets of photographic images. When the image overlap exceeds a predetermined image overlap threshold, a pair of photographic images are matched, for all of the photographic images within each composite set of photographic images to form one or more composite images.

Abstract: A computer-implemented method for moving information between computing devices includes capturing a digital image of a display of a first computing device using a camera of a second computing device, transmitting, to the first computing device, data that corresponds to the digital image; analyzing the transmitted data on the first computing device to determine whether the digital image matches a current display of the first computing device, and using the analysis to cause one of the first or second computing devices to invoke an application and match a state of an application that is executing on the other of the first or second computing devices.

Abstract: A system and method for analyzing video include segmenting video stored in computer readable storage media into keyframes. Near-duplicate keyframes are represented as a sequence of indices. The near-duplicate keyframes are rendered in a graphical representation to determine relationships between video content.

Abstract: A system and method for analyzing video include segmenting video stored in computer readable storage media into keyframes. Near-duplicate keyframes are represented as a sequence of indices. The near-duplicate keyframes are rendered in a graphical representation to determine relationships between video content.

Abstract: A system for displaying lung ventilation information, the system comprising an input (12) and a processing unit (15). The input being provided for receiving multiple CT images (71) of a lung, each CT image (71) corresponding to one phase of at least two different phases in a respiratory cycle. The processing unit (15) being configured to compare CT images (71) corresponding to different phases in the respiratory cycle for determining a deformation vector field for each phase, to generate for each phase a ventilation image (72) based on the corresponding deformation vector field, to spatially align the ventilation images (72), and to generate for at least one common position (62) in each one of the aligned ventilation images (72), a function (81) of a time course of a ventilation value for said common position (62), each ventilation value in the function (81) being based on the deformation vector fields corresponding to the aligned ventilation images (73).

Abstract: Provided is a characteristic point associating system including: a set creating unit to receive a plurality of characteristic point groups to be compared, and to create a plurality of characteristic point pair sets by grouping together characteristic point pairs that are close to one another in terms of local conversion parameter into sets; a set selecting unit to select a characteristic point pair set that contains many elements out of the plurality of characteristic point pair sets; and a corresponding characteristic point determining unit to determine out of characteristic point pairs contained in the selected characteristic point pair set, a pair of characteristic points to be associated with each other as correct corresponding characteristic points so as to be output. Thus, the characteristic point associating system associates correct pairing combinations of characteristic points that exist between the compared groups of characteristic points.

Abstract: In one embodiment, an information processing apparatus includes a calculation section, an identification section, and a notification section. The calculation section is configured to calculate similarity among a plurality of documents. The identification section is configured to identify, in response to a change made to a first document, a second document having a similarity greater than or equal to a first criterion as compared to the first document before the change. The notification section is configured to notify a user of the identified second document that the first document has been changed, in response to the change to the first document.

Abstract: A test system includes a mobile device including an evaluation application, and a host including a test automation framework (TAF). The host is configured to receive an image corresponding to a screen of the mobile device via the evaluation application and the TAF, display the received image on a screen of the host, scan the received image, and identify a portion of the received image based on a result of scanning the received image.

Abstract: A method, apparatus, and computer readable medium for identifying a person in an image includes an image analyzer. The image analyzer determines the content of an image such as a person, location, and object shown in the image. A person in the image may be identified based on the content and event data stored in a database. Event data includes information concerning events and related people, locations, and objects determined from other images and information. Identification metadata is generated and linked to each analyzed image and comprises information determined during image analysis. Tags for images are generated based on identification metadata. The event database can be queried to identify particular people, locations, objects, and events depending on a user's request.

Abstract: A system and method to classify forms. An image representing a form of an unknown document type is received. The image includes line-art. Further, a plurality of template models corresponding to a plurality of different document types is received. The plurality of different document types is intended to include the correct document type of the unknown document. A subset of the plurality of template models are selected as candidate template models. The candidate template models include line-art junctions best matching line-art junctions of the received image. One of the candidate template models is selected as a best candidate template model. The best candidate template model includes horizontal and vertical lines best matching horizontal and vertical lines of the received image, respectively, aligned to the best candidate template model.

Abstract: Providing an ID-verified blood test, in one aspect, may include enabling a user to press a finger against a fingerprint-reading panel and reading a fingerprint of the user. A blood sampling device coupled to the fingerprint-reading panel may be activated while the user has the finger against the fingerprint-reading panel to sample blood from the finger. Blood may be sampled from the user via the blood sampling device while the user has the finger against the fingerprint-reading panel. A test may be performed on the sampled blood to determine a level of specified chemical in the blood. User identification may be determined based on the fingerprint. The determined user identification and the level of the specified chemical may be returned.

Abstract: In an example embodiment, a method is provided for image categorization. Here, images are displayed. In turn, a user input that describes a characteristic shared between the images from a comparison between the images is received. The user input may then be classified into categorization data.

Abstract: Handwriting interpretation tools, such as optical character recognition (OCR), have improved over the years such that OCR is a common tool in business for interpreting typed text and sometimes handwritten text. OCR does not apply well to non-text-only diagrams, such as chemical structure diagrams. A method according to an embodiment of the present invention of interpreting a human-drawn sketch includes determining a local metric indicating whether a candidate symbol belongs to a certain classification based on a set of features. The set of features includes, as a feature, scores generated from feature images of the candidate symbol. Also included is determining a joint metric of multiple candidate symbols based on their respective classifications and interpreting the sketch as a function of the local and joint metrics.

Abstract: An image processing apparatus includes a receiving unit, a path calculation unit, and a separation unit. The receiving unit receives an image including at least a character image. The path calculation unit calculates a separation path in the image received by the receiving unit. The separation path is a line segment that separates a character image from the image. The separation unit separates the image received by the receiving unit into plural character images using a separation path calculated by the path calculation unit. The path calculation unit calculates a separation path within a predetermined range including a portion of a character image in the image so that a cumulative value of luminance values of pixels along the separation path satisfies a predetermined condition.

Abstract: An apparatus extracts a first dictionary information associated with a first category from among multiple categories included in a dictionary and second dictionary information associated with a second category from among multiple categories included in the dictionary or another dictionary, calculates a first feature amount and a second feature amount from the first dictionary information and the second dictionary information, respectively, receives an instruction as to whether or not to integrate a name of the first category and a name of the second category in the case where it is determined that a similarity between the calculated first feature amount and second feature amount is greater than a predetermined threshold and that the name of the first category and the name of the second category do not match, and integrates the name of the first category and the name of the second category with the received post-integration name.

Abstract: An image comparing system acquires a pixel value of each pixel in two images, and obtains two groups of relative values corresponding to the two images respectively. The two group of relative values is used for determining whether two images are the same.