36427 results about "Pattern recognition" patented technology

A method for determining the presence of a face from image data includes a face detection algorithm having two separate algorithmic steps: a first step of prescreening image data with a first component of the algorithm to find one or more face candidate regions of the image based on a comparison between facial shape models and facial probabilities assigned to image pixels within the region; and a second step of operating on the face candidate regions with a second component of the algorithm using a pattern matching technique to examine each face candidate region of the image and thereby confirm a facial presence in the region, whereby the combination of these components provides higher performance in terms of detection levels than either component individually. In a camera implementation, a digital camera includes an algorithm memory for storing an algorithm comprised of the aforementioned first and second components and an electronic processing section for processing the image data together with the algorithm for determining the presence of one or more faces in the scene. Facial data indicating the presence of faces may be used to control, e.g., exposure parameters of the capture of an image, or to produce processed image data that relates, e.g., color balance, to the presence of faces in the image, or the facial data may be stored together with the image data on a storage medium.

A text classifier and building the text classifier by determining appropriate parameters for the text classifier.

The invention aligns a set of plural images to construct a mosaic image. At least different pairs of the images overlap partially (or fully), and typically are images captured by a camera looking at the same scene but oriented at different angles from approximately the same location or similar locations. In order to align one of the images with another one of the images, the following steps are carried out: (a) determining a difference error between the one image and the other image; (b) computing an incremental rotation of the one image relative to a 3-dimensional coordinate system through an incremental angle which tends to reduce the difference error; and (c) rotating the one image in accordance with the incremental rotation to produce an incrementally warped version of the one image. As long as the difference error remains significant, the method continues by re-performing the foregoing determining, computing and rotating steps but this time with the incrementally warped version of the one image.

In some arrangements, product packaging is digitally watermarked over most of its extent to facilitate high-throughput item identification at retail checkouts. Imagery captured by conventional or plenoptic cameras can be processed (e.g., by GPUs) to derive several different perspective-transformed views—further minimizing the need to manually reposition items for identification. Crinkles and other deformations in product packaging can be optically sensed, allowing such surfaces to be virtually flattened to aid identification. Piles of items can be 3D-modelled and virtually segmented into geometric primitives to aid identification, and to discover locations of obscured items. Other data (e.g., including data from sensors in aisles, shelves and carts, and gaze tracking for clues about visual saliency) can be used in assessing identification hypotheses about an item. A great variety of other features and arrangements are also detailed.

A technique for hiding of data, including watermarks, in human-perceptible images, that is, image host data, is disclosed. In one embodiment a method comprises three steps. In the first step, data to be embedded is inputted. In the case of a watermark, this data is a unique signature, and may be a pseudo-noise (PN) code. In the case of hidden data to be embedded in the host data, this data is the hidden data itself, or the hidden data as spread against the frequency spectrum by a pseudo-noise (PN) code. In the second step, the inputted data is embedded within the host data, in accordance with a perceptual mask of the host data. The perceptual mask determines the optimal locations within the host data to insert the inputted data. In the case of images, these optimal locations are determined by reference to the human visual system. In the third step, the host data, with the embedded data, is further masked by a non-frequency mask. In the case of image data, the non-frequency mask is a spatial mask.

Method and system for measuring physiological parameters. The method includes capturing a sequence of images of a human face and identifying the location of the face in a frame of the video and establishing a region of interest including the face. Pixels are separated in the region of interest in a frame into at least two channel values forming raw traces over time. The raw traces are decomposed into at least two independent source signals. At least one of the source signals is processed to obtain a physiological parameter.

Systems and methods may calibrate an indicator of speed of an autonomous vehicle. In one implementation, a system may include at least one processor programmed to: receive from a camera at least a plurality of images representative of an environment of the vehicle; analyze the plurality of images to identify at least two recognized landmarks; determine, based on known locations of the two recognized landmarks, a value indicative of a distance between the at least two recognized landmarks; determine, based on an output of at least one sensor associated with the autonomous vehicle, a measured distance between the at least two landmarks; determine a correction factor for the at least one sensor based on a comparison of the value indicative of the distance between the at least to recognized landmarks and the measured distance between the at least two landmarks.

A method for generating a photolithography mask for optically transferring a pattern formed in the mask onto a substrate utilizing an imaging system. The method includes the steps of: (a) defining a set of calibration patterns, which are represented in a data format; (b) printing the calibration patterns on a substrate utilizing the given imaging system; (c) determining a first set of contour patterns corresponding to the calibration patterns imaged on the substrate; (d) generating a system pseudo-intensity function, which approximates the imaging performance of the imaging system; (e) determining a second set of contour patterns by utilizing the system pseudo-intensity function to define how the calibration patterns will be imaged in the substrate; (f) comparing the first set of contour patterns and the second set of contour patterns to determine the difference therebetween; (g) adjusting the system pseudo-intensity function until the difference between the first set of contour patterns and the second set of contour patterns is below a predefined criteria; and (h) utilizing the adjusted system pseudo-intensity function to modify the mask so as to provide for optical proximity correction.

A system and method are disclosed for generating an animatable object. A skeleton of the desired character is constructed by the user utilizing various predetermined components. These predetermined components include a various selection of rods and joints. The rods are static components which remain rigid during motion, while the various joints are moveable components. A static digitized image, for example, an image of the user, is utilized and a constructed skeleton is superimposed onto it. The desired object, such as the image of the user, can then be extracted from the background of the digital image and the resulting personal character can then be animated, for instance by selecting and dragging one of the hands with a mouse.

A method and apparatus for estimating poses of a subject by grouping data points generated by a depth image into groups representing labeled parts of the subject, and then fitting a model representing the subject to the data points using the grouping of the data points. The grouping of the data points is performed by grouping the data points to segments based on proximity of the data points, and then using constraint conditions to assign the segments to the labeled parts. The model is fitted to the data points by using the grouping of the data points to the labeled parts.

A method and system for accumulating and using images of individuals, and associated image-derived data, on an continuous basis to create recognition models that facilitate ongoing recognition of individuals in images or photo collections.

Disclosed is a method and apparatus for controlling color displayed on a color monitor. The method includes, in one embodiment, the steps of: activating a first color scheme on the monitor; responsive to the activating of the first color scheme, measuring a first color point of the monitor; storing the first color point within a memory associated with the monitor; activating a second color scheme on the monitor; responsive to the activating of the second color scheme, measuring a second color point of the monitor; storing the second color point within the memory associated with the monitor; activating a third color scheme on the monitor; responsive to the activating of the third color scheme, measuring a third color point of the monitor; and storing the third color point within the memory associated with the monitor.

The present invention is directed to generating audience analytics that includes providing a database containing a plurality of user input pattern profiles representing the group of users of terminal device, in which each user of the group is associated with one of the plurality of user input pattern profiles. A clickstream algorithm, tracking algorithm, neural network, Bayes classifier algorithm, or affinity-day part algorithm can be used to generate the user input pattern profiles. A user input pattern is detected based upon use of the terminal device by the current user and the user input pattern of the current user is dynamically matched with one of the user input pattern profiles contained in the database. The current user is identified based upon dynamic matching of the user input pattern generated by the current user with one of the user input pattern profiles. The present invention processes each user input pattern profile to identify a demographic type. A plurality of biometric behavior models are employed to identify a unique demographic type. Each user input pattern profile is compared against the plurality of biometric behavior models to match each user input pattern profile with one of the biometric behavior models such that each user input pattern profile is correlated with one demographic type. Audience analytics are then based upon the identified demographic types.

A biometric method and system for personal authentication using sequences of partial fingerprint signatures provides a high security capability to various processes requiring positive identification of individuals. This approach is further enhanced by employing a frequency domain technique for calculating a Similarity Index of the partial fingerprint signatures. In a baseline usage, the sequential partial fingerprint sequence techniques augments sentinel systems for gaining access to restricted areas, and when used in combination with financial cards, offer a unique and greatly simplified means for authenticating or identifying individuals. A highly automated technique initially obtains a reference set of linear partial fingerprint signatures which serve as reference data against which later proffered candidate data in the form of at least two linear partial fingerprint signatures are compared for authentication. The particular two candidate signatures used and the sequence in which they are submitted are selected with the user's consent and serve as a PIN-like unique personal code. In an advanced embodiment, a pair of proximity sensors located along each of the linear tracks used for developing the linear partial signatures produce finger sensing signals which compensate for finger movement speeds and hence significantly improves the calculated Similarity Index values. The use of only partial fingerprint data greatly allays the concerns of widespread fingerprint dissemination by many individuals.

A video surveillance system is set up, calibrated, tasked, and operated. The system extracts video primitives and extracts event occurrences from the video primitives using event discriminators. The extracted video primitives and event occurrences may be used to create and define additional video analytic rules. The system can undertake a response, such as an alarm, based on extracted event occurrences.

Techniques and tools for encoding and decoding motion vector information for video images are described. For example, a video encoder yields an extended motion vector code by jointly coding, for a set of pixels, a switch code, motion vector information, and a terminal symbol indicating whether subsequent data is encoded for the set of pixels. In another aspect, an encoder/decoder selects motion vector predictors for macroblocks. In another aspect, a video encoder/decoder uses hybrid motion vector prediction. In another aspect, a video encoder/decoder signals a motion vector mode for a predicted image. In another aspect, a video decoder decodes a set of pixels by receiving an extended motion vector code, which reflects joint encoding of motion information together with intra/inter-coding information and a terminal symbol. The decoder determines whether subsequent data exists for the set of pixels based on e.g., the terminal symbol.

A processor-based system operating according to digitally-embedded programming instructions includes a face detection module for identifying face regions within digital images. A normalization module generates a normalized version of the face region. A face recognition module extracts a set of face classifier parameter values from the normalized face region that are referred to as a faceprint. A workflow module compares the extracted faceprint to a database of archived faceprints previously determined to correspond to known identities. The workflow module determines based on the comparing whether the new faceprint corresponds to any of the known identities, and associates the new faceprint and normalized face region with a new or known identity within a database. The archived faceprints are digitally organized and may be selectively recalled along with their associated parent images. A database module serves to archive data corresponding to the new faceprint and its associated parent image according to the associating by the workflow module within one or more digital data storage media.

Apparatus and methods are provided for embedding or embedding digital data into an analog host or cover signal. A distributed signal feature of the cover signal in a particular domain (time, frequency or space) is calculated and compared with a set of predefined quantization values corresponding to an information symbol to be encoded. The amount of change required to modify the signal feature to the determined target quantization value is calculated and the cover signal is modified accordingly to so change the feature value over a predefined interval. Information symbols are extracted by the opposite process.

A method is presented for large media data base query and media entry identification based on multi-level similarity search and reference-query entry correlation. Media content fingerprinting detects unique features and generates discriminative descriptors and signatures used to form preliminary reference data base. The preliminary reference data base is processed and a subset-set of it is selected to form a final reference data base. To identify a media query a fast similarity search is performed first on the reference database resulting in a preliminary set of likely matching videos. For each preliminary likely matching video a further multi-level correlation is performed which includes iterative refinement, sub-sequence merging, and final result classification.

A method of determining at least one match item corresponding to a source item. A database of multiple items such as songs is created. Each song is also represented by an n-dimensional database vector in which each element corresponding to one of n musical characteristics of the song. An n-dimensional source song vector that corresponds to the musical characteristics of a source song is determined. A Distance between the source song vector and each of database song vector is calculated, each distance being a function of the differences between the n musical characteristics of the source song vector and one of source database song vector. The calculation of the distances may include the application of a weighted factor to the musical characteristics of resulting vector. A match song is selected based on the magnitude of the distance between the source song and each database songs after applying any weighted factors.

A deterministic finite automaton uses binary search (and optionally hashing) method(s) of sparse matrix representation to recognize the graphical representations of characters or icons from a bitmap representation of the computer screen. This recognition can be applied to translate data from an unknown form of original specification (file format) into a known form of representation, such as HTML. Alternatively this recognition can be applied to another process that can “see” what is on the screen, and perform programmed actions, based on what it “sees”.

An encoding device includes a color component separating unit for separating an input bit stream for the respective color components, a block dividing unit for dividing an input color component signal into blocks to generate a signal of an encoding unit area, a predicted image generating unit for generating a predicted image for the signal, a determining unit for determining a prediction mode used for encoding according to a prediction efficiency of the predicted image, a prediction error encoding unit for encoding a difference between the predicted image corresponding to the prediction mode determined by the determining unit and the input color component signal, and an encoding unit for variable length-coding the prediction mode, an output from the prediction error encoding unit, and a color component identification flag indicating the color component to which the input bit stream belongs as a result of the color component separation.

Image analysis techniques, including object recognition analysis, are applied to images obtained by one or more image capture devices deployed within inventory environments. The object recognition analysis provides object recognition data (that may include one or more recognized product instances) based on stored product (training) images. In turn, a variety of functionalities may be enabled based on the object recognition data. For example, a planogram may be extracted and compared to a target planogram, or at least one product display parameter for a product can be determined and used to assess presence of the product within the inventory environment, or to determine compliance of display of the product with a promotional objective. In yet another embodiment, comparisons may be made within a single image or between multiple images over time to detect potential conditions requiring response. In this manner, efficiency and effectiveness of many previously manually-implemented tasks may be improved.

The disclosed subject matter provides a main device and at least one secondary device. The at least one secondary device and the main device may operate in cooperation with one another and other networked components to provide improved performance, such as improved speech and other signal recognition operations. Using the improved recognition results, a higher probability of generating the proper commands to a controllable device is provided.

A method of reducing artifacts in an image previously processed by block transform encoding may comprise the steps of:

• • determining block boundaries;
  • determining an approximate metric of artifact visibility;
  • optionally interpolating across block boundaries;
  • adaptively filtering luminance;
  • optionally adaptively filtering chrominance;
  • adaptively adjusting local saturation variation; and
  • adaptively simulating high spatial frequency image detail;

wherein the adaptive steps are executed to an extent or in an amount depending on the metric or standard or measurement of artifact visibility.

Image analysis techniques, including object recognition analysis, are applied to images obtained by one or more image capture devices deployed within inventory environments. The object recognition analysis provides object recognition data (that may include one or more recognized product instances) based on stored product (training) images. In turn, a variety of functionalities may be enabled based on the object recognition data. For example, a planogram may be extracted and compared to a target planogram, or at least one product display parameter for a product can be determined and used to assess presence of the product within the inventory environment, or to determine compliance of display of the product with a promotional objective. In yet another embodiment, comparisons may be made within a single image or between multiple images over time to detect potential conditions requiring response. In this manner, efficiency and effectiveness of many previously manually-implemented tasks may be improved.

Disclosed herein is an apparatus and system for fingerprint recognition and hand-print recognition comprising a scanner with a contoured surface, or a scanner the surface of which deforms to allow more fingerprint or hand-print data to be captured, an application specific circuit for conversion of analog data from a captured fingerprint image from an embedded sensor array into a digital image and a fingerprint security application for verification of said digital image against stored fingerprint templates. The scanner array wrap with the embedded scanner array may be placed over the fixture to be scanned, or it may be formed as a part of the fixture that is scanned to authenticate the identity of a person.

A method of analyzing data based on the physiological orientation of a driver is provided. Data is descriptive of a driver's gaze-direction is processing and criteria defining a location of driver interest is determined. Based on the determined criteria, gaze-direction instances are classified as either on-location or off-location. The classified instances can then be used for further analysis, generally relating to times of elevated driver workload and not driver drowsiness. The classified instances are transformed into one of two binary values (e.g., 1 and 0) representative of whether the respective classified instance is on or off location. The uses of a binary value makes processing and analysis of the data faster and more efficient. Furthermore, classification of at least some of the off-location gaze direction instances can be inferred from the failure to meet the determined criteria for being classified as an on-location driver gaze direction instance.

Method and apparatus that use voice/audio recognition and analysis technologies to deliver assigned context sensitive information and data of interest (keywords, phrases, mood, etc.). Context sensitive information and data of interest can be extracted from any voice/audio transmissions and voice/audio recordings (or any transmission or recording that includes voice/audio) for advertising purposes. This invention includes the said assigned context sensitive information and data of interest extraction method using voice/audio recognition and analysis technologies. Most importantly, this invention opens up new doors to advertising using extracted context sensitive information and data of interest from voice/audio transmissions and recordings (or any transmission that includes voice/audio).

Methods, storage mediums, and systems for image data processing are provided. Embodiments for the methods, storage mediums, and systems include configurations to perform one or more of the following steps: background signal measurement, particle identification using classification dye emission and cluster rejection, inter-image alignment, inter-image particle correlation, fluorescence integration of reporter emission, and image plane normalization.