Abstract: An image processing apparatus includes: an obtaining member to obtain an image; a copying member to copy the image obtained by the obtaining member; a detecting member to detect a face area from the copied image or the obtained image; a correcting member to perform correction to adjust a brightness and a color shade of a whole of the obtained or copied image from which the face area is detected by the detecting member so that a flesh color component of the face area detected by the detecting member is corrected to become a predetermined status; and a synthesizing member to make a transparency of the face area detected by the detecting member different from another area and to synthesize the image corrected by the correcting member and the obtained or copied image from which the face are is not detected by the detecting member.

Abstract: In an image processing apparatus, an image acquiring section acquires one or more images. An image analysis information acquiring section acquires image analysis information on each of the one or more images. A theme determining section determines a main theme representing a theme of each group of images related to each other among the one or more images and a subtheme representing a theme of each of the one or more images based on information on photography tendencies of images associated with each of one or more themes and the image analysis information on each of the one or more images. A theme information output section outputs information on the main theme and information on the subtheme.

Abstract: The invention concerns a method for detecting raindrops on a windscreen of a vehicle, in which an image of at least an area of the windscreen is captured, wherein at least one object its extracted from the captured image, and wherein ambient light conditions are determined (S12). At least one of at least two ways of object extraction (S14, S18) is performed in dependence on the ambient light conditions. Moreover, the invention concerns a camera assembly for detecting raindrops on a windscreen of a vehicle.

Abstract: A method for recognizing a visual context in an image includes at least one step of extracting features from the image and including at least one step of coding the plurality of local descriptors developing a coding matrix by associating each local descriptor with one or a plurality of visual words in a codebook according to at least one similarity criterion, the method being characterized in that said coding step results from a compromise between the similarity between a given local descriptor and the visual words of a codebook and its resemblance to the visual words associated with the local descriptors which are spatially near to it in the domain of the image.

Abstract: A portable information handling system includes a top cover, a base, and an electronic latch. The top cover is connected to the base. The top cover has a gesture sensitive surface configured to receive a trace. The electronic latch is in communication with the gesture sensitive surface, and is configured to latch the top cover and the base together. The electronic latch is further configured to unlatch the top cover from the base in response to receiving a signal representing that the trace received on the gesture sensitive surface is proper.

Abstract: A method for authenticating the identity of a handset user is provided. The method includes: obtaining, a login account and a password from the user; judging whether the login account and the password are correct; if the login account or the password is incorrect, refusing the user to access an operating system of the handset; if the login account and the password are correct, sending the login account and the password to a cloud server, wherein the login account and the password correspond to a face sample image library of the user stored on the cloud server; acquiring an input face image of the user; sending the input face image to the cloud server; authenticating, by the cloud server, the identity of the user according to the login account, the password and the input face image.

Abstract: A computer-implemented method of providing georeferenced information regarding a location of capture of an image is provided. The method includes receiving a first image at an image-based georeferencing system, the first image comprising digital image information and identifying a cataloged second image that correlates to the first image. The method further includes automatically determining reference features common to both the second image and the first image, accessing geographic location information related to the common reference features, utilizing the geographic location information related to the common features to determine a georeferenced location of capture of the first image and providing the georeferenced location of capture for access by a user of the image-based georeferencing system.

Abstract: A method for providing object information for a scene in a wearable computer is disclosed. In this method, an image of the scene is captured. Further, the method includes determining a current location of the wearable computer and a view direction of an image sensor of the wearable computer and extracting at least one feature from the image indicative of at least one object. Based on the current location, the view direction, and the at least one feature, information on the at least one object is determined Then, the determined information is output.

Abstract: System and method are provided for determining hair tail positions. An image containing hair which is received from an image acquisition device is processed to find a coarse hair tail position. The coarse hair tail position is refined through further processing. The refined hair tail position may be used for accurate positioning, for example, of hair transplantation tools in various hair transplantation applications.

Abstract: A method for authenticating the identity of a handset user is provided. The method includes: obtaining, a login account and a password from the user; judging whether the login account and the password are correct; if the login account or the password is incorrect, refusing the user to access an operating system of the handset; if the login account and the password are correct, sending the login account and the password to a cloud server, wherein the login account and the password correspond to a face sample image library of the user stored on the cloud server; acquiring an input face image of the user; sending the input face image to the cloud server; authenticating, by the cloud server, the identity of the user according to the login account, the password and the input face image.

Abstract: A set of silhouette attributes are determined for a class of objects, where each of the silhouette attribute corresponds to a discriminative feature that is not associated with any other silhouette attribute in the set. An image content item depicting an object of the class is analyzed. A discriminative feature is identified for the object. The silhouette attribute associated with the determined discriminative feature is associated with the object as provided in the image content item.

Abstract: Systems and methods of smile detection are disclosed. An exemplary method comprises generating a search map (400) for a subset of an image (300). The method also comprises identifying a plurality of candidates (400a-f) representing mouth corners. The method also comprises generating parabolas (410) between each pair of candidates representing mouth corners. The method also comprises analyzing contour of at least one of the parabolas to determine whether the mouth curves substantially upward to form a smile or curves substantially downward to form a frown.

Abstract: The techniques discussed herein discover three-dimensional (3-D) visual phrases for an object based on a 3-D model of the object. The techniques then describe the 3-D visual phrases. Once described, the techniques use the 3-D visual phrases to detect the object in an image (e.g., object recognition).

Abstract: Disclosed is a pupil detection device capable improving the pupil detection accuracy even if a detection target image is a low-resolution image. In a pupil detection device (100), an eye area actual size calculation unit (102) acquires an actual scale value of an eye area, a pupil state prediction unit (103) calculates an actual scale prediction value of a pupil diameter, a necessary resolution estimation unit (105) calculates a target value of resolution on the basis of the calculated actual scale prediction value, an eye area image normalization unit (107) calculates a scale-up/scale-down factor on the basis of the calculated target value of resolution and the actual scale value of the eye area, and normalizes the image of the eye area on the basis of the calculated scale-up/scale-down factor, and a pupil detection unit (108) detects a pupil image from the normalized eye area image.

Abstract: An apparatus for detecting an afterimage candidate region includes: a comparison unit which compares gradation data of an n-th frame with integrated gradation data of an (n?1)-th frame and generates integrated gradation data of the n-th frame, where n is a natural number; a memory which provides the integrated gradation data of the (n?1)-th frame to the comparison unit and stores the integrated gradation data of the n-th frame; and an afterimage candidate region detection unit which detects an afterimage candidate region based on the integrated gradation data of the n-th frame, where each of the integrated gradation data of the n-th frame and the integrated gradation data of the (n?1)-th frame comprises a comparison region and a gradation region.

Abstract: An image pickup device transmits to a server a transmission sample including a detection image detected by a first detection section from a transmitting/receiving section under the control of a transmission sample control section. The server performs detection processing that requires more resources than those of the first detection section on the detection image transmitted by a second detection section from the image pickup device, and determines whether or not the detection image in question is spurious, based on a second detection score which is thereby obtained. A transmission frequency deciding section generates transmission frequency control information such as to raise the transmission frequency by an image pickup device that has a high frequency of spurious detection; a transmitting/receiving section transmits the transmission frequency control information to the image pickup device.

Abstract: Systems and methods for improving automatic selection of keeper images from a commonly captured set of images are described. A combination of image type identification and image quality metrics may be used to identify one or more images in the set as keeper images. Image type identification may be used to categorize the captured images into, for example, three or more categories. The categories may include portrait, action, or “other.” Depending on the category identified, the images may be analyzed differently to identify keeper images. For portrait images, an operation may be used to identify the best set of faces. For action images, the set may be divided into sections such that keeper images selected from each section tell the story of the action. For the “other” category, the images may be analyzed such that those having higher quality metrics for an identified region of interest are selected.

Abstract: An input image (7) having a first pixel resolution is acquired from an image capture system (2). A respective characterization of each of at least one visual quality feature of the input image (7) is determined. An output thumbnail image (9) is produced from the input image (7). The output thumbnail image (9) reflects the respective characterization of each visual quality feature. The output thumbnail image (9) has a second pixel resolution lower than the first pixel resolution. The output thumbnail image (9) is output in association with operation of the image capture system (2).

Abstract: Provided is a carried item region extraction device for accurately extracting a carried item region from an image. This carried item region extraction device has: a string region processing unit for extracting a string region including a string of a carried item from image information; and a carried item region processing unit for extracting a carried item region including a carried item from the image information on the basis of the string region.

Abstract: A method for estimating signal-dependent noise includes defining a plurality of pixel groups from among the image pixels. The method further includes computing, for one or more signal levels of the image, a difference value between two pixel groups, whereby a respective one or more difference values are computed collectively. The method determines an estimated noise response of the image as a function of the one or more computed difference values.

Abstract: Information corresponding to a face image preferred by a user as a whole is presented while considering a face element preferred by the user. An information processing apparatus identifies a priority of each of a plurality of elements included in a face in a reference face image. The priority is according to specification by a user. The information processing apparatus extracts, from among a plurality of face images, face images whose similarities of an area including the plurality of elements to the reference face image is greater than or equal to a first threshold value. The information processing apparatus decides, on the basis of similarities of each element between the reference face image and the extracted face images and the identified priority of each element, presentation order of presentation information presented as search results corresponding to the extracted face images.

Abstract: A method for content aware multimedia resizing includes selecting at least one Region Of Interest (ROI) in an input multimedia, resizing the at least one ROI, and generating an output multimedia with the resized at least one ROI. An electronic device for content aware multimedia resizing includes a processor configured to select ROI in an input multimedia, resize the at least one ROI, and generate an output multimedia with the resized at least one ROI. A computer-readable medium storing a program for content aware multimedia resizing, the program which when executed by a processor causes the processor to perform operations including selecting ROI in an input multimedia, resizing the at least one ROI, and generating an output multimedia with the resized at least one ROI.

Abstract: Disclosed herein is an image processing apparatus including an upper body feature data storage unit (110) which stores upper body directional feature data, which indicates the upper body of a person and indicates that the upper body is facing a specific direction, for each of a plurality of directions in conjunction with directional data indicative of the direction of the upper body directional feature data; and an upper body detection unit (140) which extracts upper body image data indicative of the upper body of the person from image data by reading the plurality of upper body directional feature data stored in the upper body feature data storage unit (110) in conjunction with the directional data and using each of the plurality of upper body directional feature data.

Abstract: Disclosed is an image creating device including a first obtaining unit which obtains an image including a face, a first extraction unit which extracts a face component image relating to main components of the face in the image and a direction of the face, a second obtaining unit which obtains a face contour image associated to the face in the image and a second extraction unit which extracts a direction of a face contour in the face contour image. The image creating device further includes a converting unit which converts at least one of the face component image and the face contour image based on the both directions of the face and the face contour and a creating unit which creates a portrait image by using at least one of the face component image and the face contour image being converted by the converting unit.

Abstract: An information processing apparatus includes a detector that detects a symbol image representing a symbol from content including an image, a determining unit that determines, on the basis of detail of image processing that changes a display form of the content, a display form of the symbol image in the content subjected to the image processing, and an addition indicating unit that indicates addition of the symbol image in the display form determined by the determining unit to the content subjected to the image processing.

Abstract: A computer implemented method and apparatus for analyzing image content and associating behaviors to the analyzed image content. The method comprises accessing a digital image; determining one or more patterns in the digital image; associating, based on the one or more determined patterns, a set of pre-defined behaviors with each determined pattern; and storing interactions with the digital image, wherein the interactions are associated with the behaviors.

Abstract: A system and method for performing content aware cropping/expansion may be applied to resize an image or to resize a selected object therein. An image object may be selected using an approximate bounding box of the object. The system may receive input indicating a lowest priority edge or corner of the image or object to be resized (e.g., using a drag operation). Respective energy values for some pixels of the image and/or of the object to be resized may be weighted based on their distance from the lowest priority edge/corner and/or on a cropping or expansion graph, and relative costs may be determined for seams of the image dependent on the energy values. Low cost seams may be removed or replicated in different portions of the image and/or the object to modify the image. The selected object may be resized using interpolated scaling and patched over the modified image.

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: To allow a viewer to easily understand the details of a moving image shot by an image capturing apparatus in the case where the moving image is browsed. A camerawork detecting unit 120 detects the amount of movement of an image capturing apparatus at the time of shooting a moving image input from a moving-image input unit 110, and, on the basis of the amount of movement of the image capturing apparatus, calculates affine transformation parameters for transforming an image on a frame-by-frame basis. An image transforming unit 160 performs an affine transformation of at least one of the captured image and a history image held in an image memory 170, on the basis of the calculated affine transformation parameters. An image combining unit 180 combines, on a frame-by-frame basis, the captured image and the history image, at least one of which has been transformed, and causes the image memory 170 to hold a composite image.

Abstract: Methods and apparatus for image matching using local features, in particular a method and apparatus for flexible interest point computation. The method involves producing multiple octaves of a digital image, wherein each octave of said multiple scale octaves comprises multiple layers; initiating a process comprising detection and description of interest points, wherein said process is programmed to progress layer-by-layer over said multiple layers of each of said multiple octaves, and to continue to a next octave of said multiple octaves upon completion of all layers of a current octave of said multiple octaves; upon the detection and the description of each interest point of said interest points during said process, recording an indication associated with said interest point in a memory, such that said memory accumulates indications during said process; and upon interruption to said process, returning a result being based at least on said indications.

Abstract: An image processing apparatus includes an identification unit configured to identify periodicity of a fundus image obtained by capturing an image of a fundus of an eye, and an information acquisition unit configured to acquire information indicating an imaging state of photoreceptor cells in the fundus image based on the periodicity.

Abstract: A method and apparatus for encoding a frame from a mixed content image sequence. In one embodiment, the method, executed under the control of a processor configured with computer executable instructions, comprises (i) generating, by an encoding processor, an image type mask that divides the frame into an unchanged portion, an object portion and a picture portion; (ii) producing lossless encoded content, by the encoding processor, from the object portion and the image type mask; (iii) generating, by the encoding processor, a filtered facsimile from the frame, the filtered facsimile generated by retaining the picture portion and filling the unchanged portion and the object portion with neutral image data; and (iv) producing, by the encoding processor, lossy encoded content from the filtered facsimile.

Abstract: An image processing unit includes a first feature amount storage in which a certain feature amount of a candidate of an object to be recognized in an image is stored, the image being input in a unit of frame from an imager, an image processor including a second feature amount storage in which the certain feature amount is stored when the candidate of the object corresponds to the certain feature amount stored in the first feature amount storage, and a target object detector to detect, on the basis of the second feature amount storage, the candidate of the object as a target object from the image of frames subsequent to a frame including the certain feature amount stored in the second feature amount storage, and when the target object is not detected, to detect the target object on the basis of the first feature amount storage.

Abstract: Systems and methods for measuring facial characteristics of patients. In various embodiments, the system uses a geometric pattern to determine a reference scale for an image that includes the geometric pattern and at least a portion of the patient's face. The system may determine the reference scale based at least in part on a known measurement within the geometric pattern. The known measurement may include a distance between two geometric attributes of the geometric pattern. The system may be further configured to correct for errors caused by an orientation of the geometric pattern within the image and/or distortion of the geometric pattern within the image. The geometric pattern may be disposed on a reference device that may be configured to enable a user to attach the reference device to the head of the patient or a pair of eyewear worn by the patient.

Abstract: An image analysis embodiment comprises generating a bulge mask from a digital image, the bulge mask comprising potential convergence hubs for spiculated anomalies, detecting ridges in the digital image to generate a detected ridges map, projecting the detected ridges map onto a set of direction maps having different directional vectors to generate a set of ridge direction projection maps, determining wedge features for the potential convergence hubs from the set of ridge direction projection maps, selecting ridge convergence hubs from the potential convergence hubs having strongest wedge features, extracting classification features for each of the selected ridge convergence hubs, and classifying the selected ridge convergence hubs based on the extracted classification features.

Abstract: The image acquisition unit 41 acquires an image including an object. By comparing information related to the shape of a relevant natural object that is included as the object in the target image acquired by the image acquisition unit 41, and information related to respective shapes of a plurality of types prepared in advance, at least one flower type for the natural object in question is selected. The secondary selection unit 43 then selects data of a representative image from among data of a plurality of images of different color, of the same flower type as prepared in advance, for each of at least one flower type selected by the primary selection unit 42, based on information related to color of the relevant natural object included as the object in the image acquired by the image acquisition unit 41.

Abstract: A surface definition module of a hair/fur pipeline may be used to generate a shape defining a surface and an associated volume. A control hair module may be used to fill the volume with control hairs and an interpolation module may be used to interpolate final hair strands from the control hairs.

Abstract: High quality, sharply focused images of an iris and the face of a person are acquired in rapid succession in either sequence by a single sensor and one or more illuminators, preferably within less than one second of each other, by changing the sensor settings or illumination levels between each acquisition.

Abstract: A system and method of processing an image is disclosed. A particular method of determining whether a particular pixel of an image is a feature candidate includes receiving data corresponding to a subset of a plurality of pixels surrounding the particular pixel. Each of the plurality of pixels may be from the image. The method further includes excluding the particular pixel from consideration as a feature candidate based on a comparison of values of the data to a comparison value. The comparison value may be based on an attribute value of the particular pixel and a threshold attribute value.

Abstract: According to an embodiment, an image processing apparatus includes an obtainer, a setter, a first calculator, a second calculator, and a third calculator. The obtainer obtains an image. The setter sets a plurality of first regions and a plurality of second regions on the image. Each of the first regions and the second regions includes two or more pixels, and at least one of the second regions is different in position or size from the first regions. The first calculator calculates first feature data representing an image feature of the first regions. The second calculator calculates second feature data which is a luminance gradient between the second regions. The third calculator calculates relative feature data representing a relative relationship between the first feature data and the second feature data.

Abstract: A method for creating navigable views includes receiving digital images, computing a set of feature points for each of the digital images, selecting one of the digital images as a reference image, identifying a salient region of interest in the reference image, identifying other digital images containing a region of interest similar to the salient region of interest in the reference image using the set of feature points computed for each of other digital images, designating a reference location for the salient region of interest in the reference image, aligning the other digital images to the image that contains the designated reference location, ordering the image that contains the designated reference location and the other digital images, and generating a navigable view.

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: A method and system for training a special object detector to distinguish a foreground object appearing in a sequence of frames for a target domain. The sequence of frames depicts motion of the foreground object in a non-uniform background. The foreground object is detected in a high-confidence subwindow of an initial frame of the sequence, which includes computing a measure of confidence that the high-confidence subwindow includes the foreground object and determining that the measure of confidence exceeds a specified confidence threshold. The foreground object is tracked in respective positive subwindows of subsequent frames appearing after the initial frame. The subsequent frames are within a specified short period of time. The positive subwindows are used to train the special object detector to detect the foreground object in the target domain. The positive subwindows include the subwindow of the initial frame and the respective subwindows of the subsequent frames.

Abstract: An image processing apparatus for processing image data by a plurality of pipeline-connected processing modules is provided. The apparatus includes a first pipeline processing unit configured to include a plurality of processing modules including a processing module which processes image data for every first size; and a second pipeline processing unit configured to be branched from the first pipeline processing unit and include a plurality of processing modules including a processing module which processes image data for every second size different from the first size. The second pipeline processing unit includes, at a start, a change unit configured to acquire partial image data of the first size from the first pipeline processing unit and change the partial image data of the first size into partial image data of the second size.

Abstract: The invention relates to a method for regenerating the background of digital images of a video stream comprising steps consisting in: —setting an initial background image, —cutting the unit images of the video stream into blocks b (i, j, t) and of the background image into corresponding blocks Bo (i, j, t). The method is essentially characterized in that it further includes steps consisting in: —selecting one block Bo of the background image and/or b of the frame image, and •calculating the space correlation thereof, with: •at least one block Bo of the background image at a time (t), and/or at another time (t?a), and/or •at least one block b of the frame image at a time (t), and/or at another time (t?a), and/or—updating the background image according to the calculation of the space correlation.

Abstract: One exemplary embodiment involves identifying feature matches between each of a plurality of object images and a test image, each of the feature matches between a feature of a respective object image and a matching feature of the test image, wherein there is a spatial relationship between each respective object image feature and a first landmark of the object image, the first landmark at a known location in the object image. The embodiment additionally involves estimating a plurality of locations for a second landmark for the test image, the estimated locations based at least in part on the feature matches and the spatial relationships, and estimating a final location for the second landmark from the plurality of locations for the second landmark for the test image.

Abstract: A method for determining a predictability of a media entity portion, the method includes: receiving or generating (a) reference media descriptors, and (b) probability estimations of descriptor space representatives given the reference media descriptors; wherein the descriptor space representatives are representative of a set of media entities; and calculating a predictability score of the media entity portion based on at least (a) the probability estimations of the descriptor space representatives given the reference media descriptors, and (b) relationships between the media entity portion descriptors and the descriptor space representatives. A method for processing media streams, the method may include: applying probabilistic non-parametric process on the media stream to locate media portions of interest; and generating metadata indicative of the media portions of interest.

Abstract: A method for applying a filter to data to improve data quality and/or reduce file size. In one example, a region of interest of an image is identified. A histogram is generated of pixel intensity values in the region of interest. The histogram is iteratively updated to focus (zoom) in on the highest peak in the histogram. A Gaussian curve is fitted to the updated histogram. A bilateral filter is applied to the images, where parameters of the bilateral filter are based on the parameters of the Gaussian curve.

Abstract: Important information about an object is detected using less arithmetic processing. An object detection unit generates an edge image from a color image. The object detection unit evaluates symmetry of an image included in the edge image by performing processing in accordance with the position of a target pixel. The object detection unit identifies a symmetry center pixel forming an object having symmetry. The object detection unit detects an object width for each symmetry center pixel. The object detection unit identifies the width of the object in the vertical direction based on the width of the symmetry center pixels in the vertical direction, and identifies the width of the object in the horizontal direction based on the object width identified for each symmetry center pixel.

Abstract: A method includes determining a position and length of a non-zero run in a row of a pixel map. The method also includes determining a number of neighbors for the non-zero run in a preceding row, based at least in part on the position and the length. In addition, the method includes updating a correspondence map of the non-zero run and a correspondence map of a first neighbor of the non-zero run, based at least in part on a correspondence map of a second neighbor of the non-zero run, in response to a determination that the non-zero run has at least two neighbors in the preceding row.