Abstract: A method includes receiving or capturing a digital image using a mobile device, and using a processor of the mobile device to: determine whether an object depicted in the digital image belongs to a particular object class among a plurality of object classes; determine one or more object features of the object based at least in part on the particular object class at least partially in response to determining the object belongs to the particular object class; build or select an extraction model based at least in part on the one or more determined object features; and extract data from the digital image using the extraction model. The extraction model excludes, and/or the extraction process does not utilize, optical character recognition (OCR) techniques. Related systems and computer program products are also disclosed.

Abstract: In various embodiments, methods, systems, and computer program products for determining distance between an object and a capture device are disclosed. The distance determination techniques are based on image data captured by the capture device, where the image data represent the object. These techniques improve the function of capture devices such as mobile phones by enabling determination of distance using a single lens capture device, and based on intrinsic parameters of the capture device, such as focal length and scaling factor(s), in preferred approaches. In some approaches, the distance estimation may be based in part on a priori knowledge regarding size of the object represented in the image data. Distance determination may be based on a homography transform and/or reference image data representing the object, a same type or similar type of object, in more approaches.

Abstract: A method includes capturing plural frames of video data using a mobile device. The frames are analyzed to determine whether any depict an object exhibiting one or more defining characteristics, and if so, whether those frame(s) depicting the object also satisfy one or more predetermined quality control criteria. If one or more of the frames depict the object and also satisfy the one or more predetermined quality control criteria, the method further includes automatically capturing an image of the object. Exemplary defining characteristics are specified for various types of object, particularly objects comprising documents. Related systems and computer program products are also disclosed. The presently disclosed techniques and systems represent translational developments across the fields of image processing and business process management.

Abstract: In various embodiments, methods, systems, and computer program products for processing digital images captured by a mobile device are disclosed. Myriad features enable and/or facilitate processing of such digital images using a mobile device that would otherwise be technically impossible or impractical, and furthermore address unique challenges presented by images captured using a camera rather than a traditional flat-bed scanner, paper-feed scanner, or multifunction peripheral. Notably, the presently disclosed systems and techniques enable three-dimensional reconstruction of objects depicted in image captured using a camera of a mobile device. The reconstruction corrects or compensates for perspective distortion caused by camera-based capture.

Abstract: Systems and methods for mobile image data capture and processing are disclosed. The techniques encompass receipt or capture of digital image data, detecting an object such as a document depicted in a digital image corresponding to the digital image data, processing the digital image to improve image quality, classifying the object from the processed image data, and extracting useful information from the object. Processing may improve image quality by correcting artifacts such as distortion, skew, blur, shadows, etc. common to digital images captured using mobile devices. Classification is based on identifying unique features (and/or combinations thereof) within the image data and determining whether the identified features indicate the object belongs to a class of known objects having similar characteristics, or is unique to all known classes. Extraction is based in whole or in part on object classification. All operations may be performed using mobile technology exclusively.

Abstract: A method includes storing raw or normalized video data in a computer accessible storage medium; analyzing portions of the video data with a first analytic engine to: determine whether the raw video data is within a first set of parameters; and generate with the first analytic engine a first set of processor settings; processing the raw or normalized video data with the first set of processor settings; and analyzing portions of the processed data with a second analytic engine to determine whether the processed data is within a second set of parameters; generating with the second analytic engine a second set of processor settings to reprocess the raw or normalized video data, sending the second set of processor settings to the first analytic engine; and reprocessing the raw or normalized video data with the first analytic engine using the second set of processor settings.

Abstract: A method involves: receiving an image comprising an ID; iteratively classifying the ID; and driving at least a portion of a workflow based at least in part on the classifying; wherein at least some of the classification iterations are based at least in part on comparing feature vector data, wherein a first classification iteration comprises determining the ID belongs to a particular class, and wherein each classification iteration subsequent to the first classification iteration comprises determining whether the ID belongs to a subclass falling within the particular class to which the ID was determined to belong in a prior classification iteration. Related systems and computer program products are also disclosed.

Abstract: Systems, methods, and computer program products are disclosed and include: initiating a capture operation using an image capture component of the mobile device, the capture operation comprising; capturing video data; and estimating a plurality of motion vectors corresponding to motion of the image capture component during the capture operation. The systems, techniques, and computer program products also include detecting a document depicted in the video data; tracking a position of the detected document throughout the video data; selecting a plurality of images using the image capture component of the mobile device, wherein the selection is based at least in part on: the tracked position of the detected document; and the estimated motion vectors; and generating a composite image based on at least some of the selected plurality of images.

Abstract: In various embodiments, methods, systems, and computer program products for processing digital images captured by a mobile device are disclosed. Myriad features enable and/or facilitate processing of such digital images using a mobile device that would otherwise be technically impossible or impractical, and furthermore address unique challenges presented by images captured using a camera rather than a traditional flat-bed scanner, paper-feed scanner, or multifunction peripheral. Notably, the presently disclosed systems and techniques enable three-dimensional reconstruction of objects depicted in image captured using a camera of a mobile device. The reconstruction corrects or compensates for perspective distortion caused by camera-based capture.

Abstract: A method includes capturing plural frames of video data using a mobile device. The frames are analyzed to determine whether any depict an object exhibiting one or more defining characteristics, and if so, whether those frame(s) depicting the object also satisfy one or more predetermined quality control criteria. If one or more of the frames depict the object and also satisfy the one or more predetermined quality control criteria, the method further includes automatically capturing an image of the object. Exemplary defining characteristics are specified for various types of object, particularly objects comprising documents. Related systems and computer program products are also disclosed. The presently disclosed techniques and systems represent translational developments across the fields of image processing and business process management.

Abstract: A method includes storing raw or normalized video data in a computer accessible storage medium; analyzing portions of the video data with a first analytic engine to: determine whether the raw video data is within a first set of parameters; and generate with the first analytic engine a first set of processor settings; processing the raw or normalized video data with the first set of processor settings; and analyzing portions of the processed data with a second analytic engine to determine whether the processed data is within a second set of parameters; generating with the second analytic engine a second set of processor settings to reprocess the raw or normalized video data, sending the second set of processor settings to the first analytic engine; and reprocessing the raw or normalized video data with the first analytic engine using the second set of processor settings.

Abstract: A method includes invoking an image capture interface via a mobile device; and analyzing video data captured via the capture interface. The analysis includes determining whether an object exhibiting one or more defining characteristics is depicted within the viewfinder; and if so, whether that object satisfies one or more predetermined quality control criteria. The method further includes displaying an indication of success or failure to satisfy the predetermined control criteria on the mobile device display. Where the object depicted within the viewfinder satisfies the one or more predetermined quality control criteria, the method also includes: displaying an indication that the object depicted in the viewfinder exhibits the one or more defining characteristics; automatically capturing an image of the object; and/or automatically storing to memory one or more of the frames in which the object is depicted in the viewfinder. Systems and computer program products are also disclosed.

Abstract: A method includes invoking an image capture interface via a mobile device; and analyzing video data captured via the capture interface. The analysis includes determining whether an object exhibiting one or more defining characteristics is depicted within the viewfinder; and if so, whether that object satisfies one or more predetermined quality control criteria. The method further includes displaying an indication of success or failure to satisfy the predetermined control criteria on the mobile device display. Where the object depicted within the viewfinder satisfies the one or more predetermined quality control criteria, the method also includes: displaying an indication that the object depicted in the viewfinder exhibits the one or more defining characteristics; automatically capturing an image of the object; and/or automatically storing to memory one or more of the frames in which the object is depicted in the viewfinder. Systems and computer program products are also disclosed.

Abstract: A method includes receiving or capturing a digital image using a mobile device, and using a processor of the mobile device to: determine whether an object depicted in the digital image belongs to a particular object class among a plurality of object classes; determine one or more object features of the object based at least in part on the particular object class at least partially in response to determining the object belongs to the particular object class; build or select an extraction model based at least in part on the one or more determined object features; and extract data from the digital image using the extraction model. The extraction model excludes, and/or the extraction process does not utilize, optical character recognition (OCR) techniques. Related systems and computer program products are also disclosed.

Abstract: In one embodiment, a method includes receiving a digital image captured by a mobile device; and using a processor of the mobile device: generating a first representation of the digital image, the first representation being characterized by a reduced resolution; generating a first feature vector based on the first representation; comparing the first feature vector to a plurality of reference feature matrices; and classifying an object depicted in the digital image as a member of a particular object class based at least in part on the comparing.

Abstract: System and methods for robust multiple speaker segmentation in noisy conversational speech are presented. Robust voice activity detection is applied to detect temporal speech events. In order to get robust speech features and detect speech events in a noisy environment, a noise reduction algorithm is applied, using noise tracking. After noise reduction and voice activity detection, the incoming audio/speech is initially labeled as speech segments or silence segments. With no prior knowledge of the number of speakers, the system identifies one reliable speech segment near the beginning of the conversational speech and extracts speech features with a short latency, then learns a statistical model from the selected speech segment. This initial statistical model is used to identify the succeeding speech segments in a conversation. The statistical model is also continuously adapted and expanded with newly identified speech segments that match well to the model.

Abstract: The disclosure describes methods for synthesis of accurate visible speech using transformations of motion-capture data. Methods are provided for synthesis of visible speech in a three-dimensional face. A sequence of visemes, each associated with one or more phonemes, are mapped onto a three-dimensional target face, and concatentated. The sequence may include divisemes corresponding to pairwise sequences of phonemes, wherein the diviseme is comprised of motion trajectories of a set facial points. The sequence may also include multi-units corresponding to words and sequences of words. Various techniques involving mapping and concatenation are also addressed.

Abstract: The present invention provides a dispersion compensator which utilizes a Virtually Imaged Phased Array (VIPA), gratings, and birefringent wedges to moderate chromatic dispersion, dispersion slope and polarization mode dispersion, and a method and system for testing such a dispersion compensator.