Abstract: An image recognition apparatus using a scalable compact local feature descriptor is provided. The image recognition apparatus includes a feature descriptor generator, a database, and a descriptor matcher. The feature descriptor generator extracts scalable compact local feature descriptor information for recognizing an object from input image information. The database includes information on a plurality of feature descriptors. The descriptor matcher compares a feature descriptor output from the feature descriptor generator with a plurality of feature descriptors stored in the database to recognize an object included in an image.

Abstract: The present invention discloses an object detection apparatus and method. A feature extracting section of the present invention comprises: a feature point extracting section, for extracting a combination of predetermined feature point pairs from an image; a pixel value obtaining section, for obtaining a pixel value of each feature point in the combination of feature point pairs; a feature point comparing section, for comparing, in accordance with the pixel values obtained by the pixel value obtaining section, two feature points in each feature point pair to obtain a logical value; and an feature obtaining section, for determining the feature of the image in accordance with the logical value.

Abstract: A system for performing an image categorization procedure includes an image manager with a keypoint generator, a support region filter, an orientation filter, and a matching module. The keypoint generator computes initial descriptors for keypoints in a test image. The support region filter and the orientation filter perform respective filtering procedures upon the initial descriptors to produce filtered descriptors. The matching module compares the filtered descriptors to one or more database image sets for categorizing said test image. A processor of an electronic device typically controls the image manager to effectively perform the image categorization procedure.

Abstract: A technology for creating an arbitrary viewpoint image with high quality based on pixel value information as seen from a single viewpoint and real spatial positional information has not been known. A hidden point is extracted based on a relative positional relationship between a single viewpoint closed surface projection point for arbitrary measurement point and neighboring projection point, a relative positional relationship between other viewpoint closed surface projection point for arbitrary measurement point and neighboring projection point, distance from arbitrary measurement point to another viewpoint, and distance from measurement point projected onto neighboring projection point on the other viewpoint closed surface to another viewpoint.

Abstract: An image processing apparatus executes smoothing processing (reduction conversion) of an input image to acquire a smoothed image (reduced image), acquires a normalization parameter for normalization from the smoothed image, and normalizes pixel values of the input image based on the normalization parameter.

Abstract: A data correction apparatus which corrects data associated with an image of an object projects vector data obtained by connecting data to be corrected to each other onto a subspace to generate a dimensionally reduced projection vector, and executes dimension restoration processing in which the dimensionality of the projection vector is restored to generate dimensionally restored vector data, thereby generating a plurality of dimensionally restored vector data for each type of fluctuation. The data correction apparatus determines the fluctuation of the object based on the projection vector, integrates the plurality of dimensionally restored vector data with each other based on the determination result, and outputs the integration result as corrected data.

Abstract: A technique for efficient processing of annotations in images such as panoramic images is herein disclosed. In an embodiment, a first user annotation is received for a feature in a first panorama, and a second user annotation for the same feature is received in a second panorama. The coordinates for the feature can then be generated by computing the intersection between data generated for the first user annotation and for the second user annotations.

Abstract: The present invention discloses a control unit, a video device employing said control unit and a control method thereof, wherein the control unit includes: a recognition device which is used to recognize the target in the target image; a calculation device which is used to calculate and transform the position coordinate of the recognized imaging target from the recognition device and output the position of the operation unit.

Abstract: A line width measuring device includes an acquisition unit, an extraction unit, and a generation unit. The acquisition unit that acquires a binary image that is obtained by reading a medium having a line width sample printed thereon with an image reading device, the line width sample representing output characteristics regarding a line width of an image forming device. The extraction unit that extracts a displacement amount of steps that are repeatedly generated in an image corresponding to the line width sample in the binary image by reading the medium with the image reading device in an orientation such that the line width sample has an angle ? (0°<?<90°) with respect to a main scanning direction of image reading. The generation unit that generates line width information regarding a width of the line width sample by using the displacement amount extracted by the extraction unit.

Abstract: A method for recognition of a predetermined pattern in an image data set recorded by a device for recording of at least two electromagnetic frequency spectra is provided. A first difference value is formed for the image points of the selected area as a function of a difference between a data vector of a corresponding image point and a first reference data vector. A second difference value is formed for an image point of a selected area as a function of a difference between the data vector of this image point and a second reference data vector. A predetermined pattern is recognized when it is determined at least one pattern correlation quantity is below a predetermined threshold value and a local minimum is present.

Abstract: There is provided an information processing apparatus including an image acquisition unit configured to acquire images captured from a plurality of observation points for a predetermined object, a feature point extraction unit configured to extract a feature point in each of the images acquired by the image acquisition unit, a correspondence relationship acquisition unit configured to acquire a correspondence relationship of the feature points based on images from among adjacent observation points, and an information presentation unit configured to quantitatively present information about the correspondence relationship acquired by the correspondence relationship acquisition unit.

Abstract: Identification of objects in images. All images are scanned for key-points and a descriptor is computed for each region. A large number of descriptor examples are clustered into a Vocabulary of Visual Words. An inverted file structure is extended to support clustering of matches in the pose space. It has a hit list for every visual word, which stores all occurrences of the word in all reference images. Every hit stores an identifier of the reference image where the key-point was detected and its scale and orientation. Recognition starts by assigning key-points from the query image to the closest visual words. Then, every pairing of the key-point and one of the hits from the list casts a vote into a pose accumulator corresponding to the reference image where the hit was found. Every pair key-point/hit predicts specific orientation and scale of the model represented by the reference image.

Abstract: An image judgment device stores element characteristic information for each element of a characteristic part of a sample object and first and second positional information defining a position of each element, selects the first or the second positional information, and acquires image characteristic information for a partial image in an image frame considered as an element specified by the first positional information based on a first axis. The image judgment device also extracts image characteristic information for a partial image in an image frame considered as an element specified by the second positional information based on a second axis (which is acquired by rotating the first axis), specifies element characteristic information for an element corresponding to a position of the partial image, and judges whether the characteristic part appears in the image frame with use of the specified element characteristic information and the extracted image characteristic information.

Abstract: Disclosed herein is an image processor including: a feature point extraction section adapted to extract the feature points of an input image; a correspondence determination section adapted to determine the correspondence between the feature points of the input image and those of a reference image using a feature point dictionary; a feature point coordinate distortion correction section adapted to correct the coordinates of the feature points of the input image corresponding to those of the reference image; a projection relationship calculation section adapted to calculate the projection relationship between the input and reference images; a composite image coordinate transform section adapted to generate a composite Image to be attached from a composite image; and an output image generation section adapted to merge the input image with the composite image to be attached.

Abstract: A computer implemented method computer implemented method for deriving a fingerprint from video data is disclosed, comprising the steps of receiving a plurality of frames from the video data; selecting at least one key frame from the plurality of frames, the at least one key frame being selected from two consecutive frames of the plurality of frames that exhibiting a maximal cumulative difference in at least one spatial feature of the two consecutive frames; detecting at least one 3D spatio-temporal feature within the at least one key frame; and encoding a spatio-temporal fingerprint based on mean luminance of the at least one 3D spatio-temporal feature. The least one spatial feature can be intensity. The at least one 3D spatio-temporal feature can be at least one Maximally Stable Volume (MSV).

Abstract: An object of the present invention is to provide a positioning system which makes it possible to perform positioning processing in a positioning target mobile object with a smaller calculation amount. A scenery image database according to an aspect of the present invention is characterized by comprising a plurality of scenery image data and image acquisition locations at which the scenery image data have been acquired are correlated with each other and stored, wherein each of the plurality of scenery image data include a feature amount of a feature point corresponding to a thing other than a thing of which a location or a shape is unlikely to be kept as it is on the real world during a period larger than or equal to a predetermined period.

Abstract: An image processing device includes a tracking unit to track a predetermined point on an image as a tracking point, to correspond with a first operation. The image processing device also includes a display control unit to display tracking point candidates, which are greater in number than objects on the image and fewer than the number of pixels of the image, on the image, at an equidistant spacing. Further the image processing device includes a setting unit to set one of the tracking point candidates as a tracking point on a next frame of the tracking unit, in response to an instruction of the one of the tracking point candidates during a display of the tracking point candidates at the equidistant spacing.

Abstract: A method for following hand movements in an image flow, includes receiving an image flow in real time, locating in each image in the received image flow a hand contour delimiting an image zone of the hand, extracting the postural characteristics from the image zone of the hand located in each image, and determining the hand movements in the image flow from the postural characteristics extracted from each image. The extraction of the postural characteristics of the hand in each image includes locating in the image zone of the hand the center of the palm of the hand by searching for a pixel of the image zone of the hand the furthest from the hand contour.

Abstract: Provided is an image stabilizing apparatus and method for correcting an image that is shaken due to a movement of a camera. The image stabilizing apparatus includes a characterizing point checking region setting unit including: a sample frame extract unit which extracts a plurality of image frames obtained for a certain period of time in image data obtained by photographing an object; and a frame analyzing unit which detects a plurality of characterizing points in the extracted plurality of image frames, and sets a characterizing point checking region which is used to check characterizing points in a currently input image frame.

Abstract: In accordance with an embodiment, a method of authenticating images includes electronically receiving an anchor image and a query image, performing a feature point extraction of an anchor image, and performing a feature point extraction of a query image. The method also includes clustering feature points of the anchor image and feature points of the query image, where clustering includes determining matching feature points, determining outlier feature points, and excluding outlier feature points. Whether the anchor image is similar to the query image is determined based on a distance between the feature points of the anchor image and the feature points of the query image. If the anchor image is similar to the query image, possible tampered areas of the query image based on the outlier feature points are identified.

Abstract: A position measuring apparatus including a first irradiating part that irradiates a first beam to an object, a second irradiating part that irradiates a second beam to the object, a capturing part that captures images of the object, a processing part that generates a first difference image and a second difference image by processing the images captured by the capturing part, an extracting part that extracts a contour and a feature point of the object from the first difference image, a calculating part that calculates three-dimensional coordinates of a reflection point located on the object based on the second difference image, and a determining part that determines a position of the object by matching the contour, the feature point, and the three-dimensional coordinates with respect to predetermined modeled data of the object.

Abstract: A system and a method for progressive queries, which are a sequence of queries for visual search of an image, sent from a sender to a receiver of a communication network, are disclosed. Queries based on a set of feature points and their associated locations of an image may be selected in sequence. A sender sends a first query to a receiver, wherein the first query comprises a number of feature points which is a subset of the set of feature points of the image invariant to rotation and scaling in creating the image. The sender receives a feedback from the receiver, wherein the feedback is generated by the receiver based on searching an image repository using information from the first query. The sender then decides whether there is a match of the image in the image repository based on the received feedback.

Abstract: An apparatus for calculating spatial coordinates is disclosed. The apparatus may extract a plurality of feature points from an input image, calculate a direction vector associated with the feature points, and calculate spatial coordinates the feature points based on a distance between the feature points and the direction vector.

Abstract: A distribution evaluation apparatus includes an evaluation value calculating unit that calculates weighted energy, as an evaluation value representing distribution of located objects x and y, by calculating a product resulting from multiplying weighting function values ?(x) and ?(y) and probability density function values ?(x) and ?(y) representing densities or sizes of the located objects x and y, by a mutual influence value determined by a function fr having as a variable a distance between the located objects x and y, and then by summing the resulting products with respect to all the located objects x and y into the weighted energy, and an evaluating unit that evaluates the distribution of the located objects in accordance with the evaluation value calculated by the evaluation value calculating unit.

Abstract: An image stabilization method and an image stabilization device are provided. In the method, each of images to be processed is detected by a feature point detection method to detect a plurality of feature points. The relationship of the same feature points in adjacent images to be processed is analyzed. According to the relationship of the feature points, a homography transform matrix of adjacent images to be processed is calculated. Based on the known feature points and the homography transform matrix, a stabilization matrix and a plurality of adjustment matrices corresponding to each image to be processed are calculated. Compensation is performed on each image to be processed by the adjustment matrices, so as to produce a plurality of corrected images. A first image of adjacent corrected images multiplied by the same stabilization matrix is transformed to a second image of the adjacent corrected images.

Abstract: Object recognition can be improved by verifying a geometric consistency between matching interesting points pairs of two images, as objects with the images are more likely to match when the matching interesting points pairs are geometrically consistent. The geometric consistency between matching interesting points pairs can be verified in accordance with a topology code distance vector (D). The topology code distance vector (D) may be evaluated in accordance with a decision tree classifier, which may be trained in accordance with previous or historic topology code distance vectors. The topology code distance vector (D) may be computed from a subset of matching interesting points pairs having the shortest matching distance.

Abstract: An image processing apparatus to obtain highly reliable local feature point and local feature amount. With the number of local feature points as a factor of an image local feature amount description size, the reproducibility of the local feature point and local feature amount is estimated, and description is made by the local amount description size, sequentially from local feature point and local feature amount with the highest reproducibility. It is possible to ensure a local feature amount description size and search accuracy.

Abstract: A method and system characterizes an image of an object. A plurality of interest points are detected within a first image and a local image feature descriptor is built for at least some of the interest points, including mapping information about the interest points according to at least circular distribution information.

Abstract: 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.

Abstract: An image processing apparatus includes: an image transformation parameter calculation device which calculates an image transformation parameter for matching an acquired first image and a second image with each other among detected plurality of corresponding points; an image transformation device which transforms the second image using the calculated image transformation parameter and acquires the transformed image as a third image; and a feature point existing region determination device which determines whether or not the feature point extracted from the first image is positioned in an invalid image region at an edge of the image, the invalid image region being generated by execution of a predetermined filtering process on the first image, wherein the corresponding point detection device tracks the feature point determined that the feature point extracted from the first image is positioned in the invalid image region, using the first image and the third image.

Abstract: A pattern recognition apparatus including: an extracting section for extracting, from a query image that is composed of at least one piece of pattern component and previously undergoes a geometric transformation, the pattern component; a feature acquiring section for acquiring a geometric invariant feature of the pattern component as a query feature, the query feature being represented by at least three feature points including first, second and third feature points, each feature point locating on the pattern component and being retrieved from the pattern component based on a predetermined rule; a comparing section for comparing the query feature with a plurality of reference features, each reference feature representing different reference patterns prepared as candidates for pattern recognition; and a pattern determination section for determining, as a recognition result, a specific reference pattern out of the candidates based on a similarity of features therebetween and, wherein: each reference feature is

Abstract: The invention relates to a method for estimating an image relation model for two or more related images based on a plurality of point correspondences. The method includes using a weighted random sampling algorithm to repeatedly draw subsets of point correspondences for generating model estimates, evaluating said model estimates for the full plurality of the point correspondences, and updating weights associated with each of the point correspondences in the random sampling algorithm based on information obtained in said evaluating.

Abstract: Aspects of the present invention are related to systems and methods for determining the location of numerals in an electronic document image.

Abstract: Embodiments of the invention are directed to using image data and contextual data to determine information about a scene, based on one or more previously obtained images. Contextual data, such location of image capture, can be used to determine previously obtained images related to the contextual data and other location-related information, such as billboard locations. With even low resolution devices, such as cell phone, image attributes, such as a histogram or optically recognized characters, can be compared between the previously obtained images and the newly captured image. Attributes matching within a predefined threshold indicate matching images. Information on the content of matching previously obtained images can be provided back to a user who captured the new image. User profile data can refine the content information. The content information can also be used as search terms for additional searching or other processing.

Abstract: Systems, methods, and apparatus, including software tangibly stored on a computer readable medium, involve image processing. An image processing graph includes multiple nodes that each correspond to an image processing operation. Input image data relating to a particular input image is received. Region of interest data defining an output image region to be generated based on the input image data is received. A domain of defined node output data is identified for each of the nodes using the input image data, and the graph is traversed in a first traversal order. An identification of the first traversal order is stored. A region of requested node output data is identified for each of the nodes using the region of interest data, and the graph is traversed in a second traversal order. The second traversal order is based at least in part on the stored identification of the first traversal order.

Abstract: A plate solving methodology determines celestial coordinates of an image. Star locations are extracted from the image in terms of pixel coordinates. A group of four stars, referred to as a “test quad”, is identified. A signature for the test quad is generated. In one embodiment, this test signature is derived by determining the separations of the four stars in the test quad, normalized by the largest separation. In one embodiment, the signature also includes the sum of these normalized separations. A query is performed, using the generated signature, against a database of reference signatures for known groups of stars (referred to as “reference quads”). A geometric transform is determined, establishing the relationship between the test quad and a reference quad that matches within a specified tolerance. This geometric transform defines the celestial coordinates of the image. Additional verification steps can be performed to confirm the accuracy of the match.

Abstract: Disclosed is a vanishing point detecting system that includes a straight line detecting unit, a vanishing point detecting unit, and a vanishing point outputting unit. In the vanishing point detecting unit, a vanishing point is detected with one evaluation index of vanishing point plausibility being whether or not angles of plural straight lines passing through a point in question or a vicinity thereof are sparsely distributed over a relatively wide range.

Abstract: A method for processing a sequence of images. In an embodiment, one or more training datasets are analyzed having a sequence of images showing a first condition and a sequence of images showing a second condition. A multivariate regression model is used to determine a relationship between relative positions of one or more features in the sequence of images showing the first condition and relative positions of the one or more features in the sequence of images showing the second condition. In an embodiment, the determined relationship is used to predict positions of the one or more features in an inquire sequence of images showing the second condition given an inquire sequence of images showing the first condition. The predicted positions can then be refined using various methods. In an embodiment, sequences of images are aligned to a common time scale.

Abstract: An information processing device includes: an outline extraction unit extracting an outline of a subject from a picked-up image of the subject; a characteristic amount extraction unit extracting a characteristic amount, by extracting sample points from points making up the outline, for each of the sample points; an estimation unit estimating a posture of a high degree of matching as a posture of the subject by calculating a degree of the characteristic amount extracted in the characteristic amount extraction unit being matched with each of a plurality of characteristic amounts that are prepared in advance and represent predetermined postures different from each other; and a determination unit determining accuracy of estimation by the estimation unit using a matching cost when the estimation unit carries out the estimation.

Abstract: The present disclosure provides a microscopic vision measurement method based on the adaptive positioning of the camera coordinate frame which includes: calibrating parameters of a microscopic stereo vision measurement model (201); acquiring pairs of synchronical images and transmitting the acquired images to a computer through an image acquisition card (202); calculating 3D coordinates of feature points in a scene according to the matched pairs of feature points in the scene obtained from the synchronical images and the calibrated parameters of the microscopic stereo vision measurement model (203); and performing specific measurement according to the 3D coordinates of the feature points in the scene (204). With the method, the nonlinearity of the objective function in the microscopic vision calibration optimization is effectively decreased and a better calibration result is obtained.

Abstract: An image processing apparatus includes a modification processing unit configured to modify an input image by distributing a value of each of pixels in the input image over a two-dimensional distribution area having a randomly different size and direction in accordance with modification characteristic information for distributing each pixel over the distribution area. The modification characteristic information is information for modifying the input image using a modification characteristic which is randomly different for each pixel position.

Abstract: Various embodiments of methods and apparatus for facial retouching are disclosed. In one embodiment, a face in an input image is detected. One or more transformation parameters for the detected face are estimated based on a profile model. The profile model is applied to obtain a set of feature points for each facial component of the detected face. Global and component-based shape models are applied to generate feature point locations of each facial component of the detected face.

Abstract: Various embodiments of methods and apparatus for facial retouching are disclosed. In one embodiment, a face in an input image is detected. Independent sets of feature points are detected for respective facial feature components. A plurality of masks for each of the facial feature components is generated. Using the plurality of masks, retouch effects are performed to the facial feature components. Some embodiments provide for user interaction to constrain the mask generation.

Abstract: An image search method may include: determining a quadrant of a predicted motion vector; calculating a tilt value of a first reference frame and a tilt value of a second reference frame using the predicted motion vector; deciding a search area for uneven hexagon search in response to the quadrant of the predicted motion vector and the calculated tilt values; performing the uneven hexagon search with respect to the decided search area; and/or comparing a result of the performed uneven hexagon search with a threshold value to determine termination of the uneven hexagon search. The second reference frame is earlier-in-time relative to the first reference frame.

Abstract: A method for comparing videos includes detecting local features in frames of a video and determining the positions of detected local features in a first frame compared to their respective positions in a succeeding second frame. For at least some of the detected local features, a movement indicator is generated representing the position of a local feature in the first frame relative to the position of that local feature in the second frame, the movement indicator including an orientation, to obtain a plurality of movement indicators. Movement indicators are grouped by orientation ranges. The number of grouped movement indicators in an orientation range are summed to obtain a value for that orientation range. A time series of values for at least one given orientation range is obtained by determining the positions of detected local features in a first frame compared to their respective positions in a succeeding second frame for a plurality of pairs of frames.

Abstract: An image processing method and apparatus for tamper proofing are proposed. The method includes: acquiring a first robust feature representation of a first set of robust feature points for an original image and a second robust feature representation of a second set of robust feature points for an image to be detected, respectively; matching the first robust feature representation with the second robust feature representation so as to acquire mismatching feature points; and determining whether the image to be detected has been tampered with relative to the original image based on a distribution characteristic of the mismatching feature points. With the embodiments of the invention, the distribution characteristic of the mismatching feature points is analyzed based on the robust feature representations of the original image and the image to be detected, so that conventional operations on the image can be distinguished effectively from tampering in the image with sufficient robustness.

Abstract: The present invention provides an apparatus for measuring a location and a distance of an object by using a camera including: a camera module for photographing an external image; a parameter setup unit for setting internal and external parameters of the camera module; an image processor unit for receiving a captured image of an image photographed from the camera module, extracting a target object within the captured image, and extracting specific point coordinates of the extracted target object; and a location and distance calculating unit for calculating three-dimensional object location information in a two-dimensional camera coordinate system through the internal and external parameters of the camera module and coordinates of the target object, and calculating distance information from the location information of the object.

Abstract: An information processing apparatus includes a model image obtaining unit configured to obtain a plurality of model images; a model image feature quantity extracting unit configured to extract feature quantities of the model images obtained by the model image obtaining unit; a matching unit configured to perform matching on the feature quantities of the model images extracted by the model image feature quantity extracting unit; and an identifying feature point extracting unit configured to extract, as a result of the matching performed by the matching unit, feature points having a low correlation with a predetermined model image in similar model images that are the model images having a predetermined number or more of the feature quantities that match feature quantities of the predetermined model image, the extracted feature points being regarded as identifying feature points used for identification of the respective similar model images.

Abstract: Contact-less remote-sensing crack detection and/quantification methodologies are described, which are based on three-dimensional (3D) scene reconstruction, image processing, and pattern recognition. The systems and methodologies can utilize depth perception for detecting and/or quantifying cracks. These methodologies can provide the ability to analyze images captured from any distance and using any focal length or resolution. This adaptive feature may be especially useful for incorporation into mobile systems, such as unmanned aerial vehicles (UAV) or mobile autonomous or semi-autonomous robotic systems such as wheel-based or track-based radio controlled robots, as utilizing such structural inspection methods onto those mobile platforms may allow inaccessible regions to be properly inspected for cracks.

Abstract: An image processing apparatus includes: a first distribution calculation unit calculating a distribution of luminance gradient vectors in a first local area that includes a feature point on an image; a second distribution calculation unit calculating distributions of the luminance gradient vectors in second local areas close to the feature point on the image; a selection unit comparing the distribution of the luminance gradient vectors of the first local area with the distributions of the luminance gradient vectors of the second local areas to select the most different distribution of the luminance gradient vectors of the second local area; and a feature descriptor calculation unit calculating a feature descriptor at the feature point on the basis of the distribution of the luminance gradient vectors of the first local area and the distribution of the luminance gradient vectors of the second local area selected by the selection unit.