Abstract: The present disclosure discloses method and system for extracting relevant entities from a text corpus. The method comprises receiving, by the entity extraction computing device, a text corpus and an entity, determining at least one feature for each block of text from the text corpus, where the at least one feature corresponds to predefined one or more feature heads, calculating a score for each block of text from the text corpus based on training of the entity extraction system, determining a template from one or more templates based on the score, where the one or more templates are generated based on the training of the entity extraction system, and extracting at least one relevant entity from the text corpus, with respect to the entity, based on the template. The method and system disclosed in the present disclosure may be used to extract relevant entities across various domains by training the system.

Abstract: A method, system and computer program product for conducting an online auction of a plurality of heterogeneous items between a plurality of selling and potential purchasing parties. The method includes the steps of accepting an offer in respect of an item, accepting one or more subsequent offers that is/are preferable to a previously accepted offer, and rejecting the previously accepted offer. While the offer/s is/are binding on a party making the offer, acceptance of the offer/s is/are not binding on a party accepting the offer. Classes of “seller strategies”, for offering items to potential purchasing parties, and “buyer strategies”, to decide which offers to accept, are also disclosed. As a result of the interaction of the buyer and seller strategies, the auction mechanism converges to an allocation of items to buyers at particular prices and assists in discovering a free and fair competitive equilibrium price.

Abstract: In one aspect, a method and system are described for receiving input for a virtual user in a virtual environment. The input may be based on a plurality of movements performed by a user accessing the virtual environment. Based on the plurality of movements, the method and system can include detecting that at least one portion of the virtual user is within a threshold distance of a collision zone, the collision zone being associated with at least one virtual object. The method and system can also include selecting a collision mode for the virtual user based on the at least one portion and the at least one virtual object and dynamically modifying the virtual user based on the selected collision mode.

Abstract: A system for tracking a first electronic device, such as a handheld electronic device, in a virtual reality environment generated by a second electronic device, such as a head mounted display may include the fusion of data collected by sensors of the electronic device with data collected by sensors of the head mounted display, together with data collected by a front facing camera of the electronic device related to the front face of the head mounted display.

Abstract: Systems and methods for modeling functional magnetic resonance image datasets using a multivariate auto-regressive model which captures temporal dynamics in the data, and creates a reduced representation of the dataset representative of functional connectivity of voxels with respect to brain activity. Raw spatio-temporal data is processed using a multivariate auto-regressive model, wherein coefficients in the model with high weights are retained as indices that best describe the full spatio-temporal data. When there are a relatively small number of temporal samples of the data, sparse regression techniques are used to build the model. The model coefficients are used to perform data processing functions such as indexing, prediction, and classification.

Abstract: Systems and methods are disclosed for gesture-initiated actions in videoconferences. In one implementation, a processing device receives one or more content streams as part of a communication session. The processing device identifies, within the one or more content streams, a request for feedback. The processing device processes, based on an identification of a request for feedback within the one of the plurality of content streams, the one or more content streams to identify a presence of one or more gestures within at least one of the one or more content streams. The processing device initiates, based on an identification of the presence of one or more gestures within at least one of the one or more content streams, an action with respect to the communication session.

Abstract: A system and method for data anonymization using hierarchical data clustering and perturbation is provided. The system includes a computer system and an anonymization program executed by the computer system. The system converts the data of a high-dimensional dataset to a normalized vector space and applies clustering and perturbation techniques to anonymize the data. The conversion results in each record of the dataset being converted into a normalized vector that can be compared to other vectors. The vectors are divided into disjointed, small-sized clusters using hierarchical clustering processes. Multi-level clustering can be performed using suitable algorithms at different clustering levels. The records within each cluster are then perturbed such that the statistical properties of the clusters remain unchanged.

Abstract: Systems, methods, and computer storage mediums are provided for creating a scene scan from a group of photographic images. An exemplary method includes determining a set of common features for at least one pair of photographic images. The features include a portion of an object captured in each of a first and a second photographic image included in the pair. The first and second photographic images may be captured from different optical centers. A similarity transform for the at least one pair of photographic images is the determined. The similarity transform is provided in order to render the scene scan from each pair of photographic images. At least one of the rotation factor, the scaling factor, or the translation factor associated with the similarity transform is used to position each pair of photographic images such that the set of common features between a pair of, at least in part, align.

Abstract: Systems, methods and articles of manufacture for generating sequences of face and expression aligned images are presented. An embodiment includes determining a plurality of candidate images, computing a similarity distance between an input image and each of the candidate images based on facial features in the input image and the candidate images, comparing the computed similarity distances, selecting a candidate image based on the comparing, and adding the selected candidate image to an image sequence for real-time display. Embodiments select images from the image sequence as they are being added to the image sequence and scale, rotate and translate each image so that a face appearing in a selected image is aligned with a face appearing in a subsequently selected image from the image sequence. In this way, embodiments are able to render arbitrarily large image collections efficiently and in real time to display a face and expression aligned movie.

Abstract: Systems and methods for modeling functional magnetic resonance image datasets using a multivariate auto-regressive model which captures temporal dynamics in the data, and creates a reduced representation of the dataset representative of functional connectivity of voxels with respect to brain activity. Raw spatio-temporal data is processed using a multivariate auto-regressive model, wherein coefficients in the model with high weights are retained as indices that best describe the full spatio-temporal data. When there are a relatively small number of temporal samples of the data, sparse regression techniques are used to build the model. The model coefficients are used to perform data processing functions such as indexing, prediction, and classification.

Abstract: Systems and methods for reducing the peak-to-average ratio (PAR) at the transmitter can reduce the dynamic range required in various analog components. PAR can be reduced by applying a time-domain compensation signal which reduces the magnitude of peaks in the time-domain signal prior to transmission where the time-domain compensation signals use tones that are reserved for the purpose of reducing the PAR. The reservation of these reserved tones for PAR can be implemented by altering the typical startup procedures in a digital subscriber line (xDSL) system. The use of the reserved tones to reduce the PAR can be implemented using a low complexity algorithm or using an adaptive technique.

Abstract: Systems and methods for modeling functional magnetic resonance image datasets using a multivariate auto-regressive model which captures temporal dynamics in the data, and creates a reduced representation of the dataset representative of functional connectivity of voxels with respect to brain activity. Raw spatio-temporal data is processed using a multivariate auto-regressive model, wherein coefficients in the model with high weights are retained as indices that best describe the full spatio-temporal data. When there are a relatively small number of temporal samples of the data, sparse regression techniques are used to build the model. The model coefficients are used to perform data processing functions such as indexing, prediction, and classification.

Abstract: System and method for image detection that include collecting image data; at a processor, over a plurality of support regions of the image data, computing a dimensionality component of a support region of the image data, wherein the, non-nucleus pixels of a support region; calculating a normalizing factor of the dimensionality component; for at least one weighted pattern of a pattern set, applying a weighted pattern to the dimensionality component to create a gradient vector, mapping the gradient vector to a probabilistic model, and normalizing the gradient vector by the normalizing factor; condensing probabilistic models of the plurality of support regions into a probabilistic distribution feature for at least one cell of the image data; applying a classifier to at least the probabilistic distribution feature; and detecting an object in the image data according to a result of the applied classifier.

Abstract: Systems, methods and articles of manufacture for generating sequences of face and expression aligned images are presented. An embodiment includes determining a plurality of candidate images, computing a similarity distance between an input image and each of the candidate images based on facial features in the input image and the candidate images, comparing the computed similarity distances, selecting a candidate image based on the comparing, and adding the selected candidate image to an image sequence for real-time display. Embodiments select images from the image sequence as they are being added to the image sequence and scale, rotate and translate each image so that a face appearing in a selected image is aligned with a face appearing in a subsequently selected image from the image sequence. In this way, embodiments are able to render arbitrarily large image collections efficiently and in real time to display a face and expression aligned movie.

Abstract: Systems, methods and articles of manufacture for generating sequences of face and expression aligned images are presented. An embodiment includes determining a plurality of candidate images, computing a similarity distance between an input image and each of the candidate images based on facial features in the input image and the candidate images, comparing the computed similarity distances, selecting a candidate image based on the comparing, and adding the selected candidate image to an image sequence for real-time display. Embodiments select images from the image sequence as they are being added to the image sequence and scale, rotate and translate each image so that a face appearing in a selected image is aligned with a face appearing in a subsequently selected image from the image sequence. In this way, embodiments are able to render arbitrarily large image collections efficiently and in real time to display a face and expression aligned movie.

Abstract: A system and method for data anonymization using hierarchical data clustering and perturbation is provided. The system includes a computer system and an anonymization program executed by the computer system. The system converts the data of a high-dimensional dataset to a normalized vector space and applies clustering and perturbation techniques to anonymize the data. The conversion results in each record of the dataset being converted into a normalized vector that can be compared to other vectors. The vectors are divided into disjointed, small-sized clusters using hierarchical clustering processes. Multi-level clustering can be performed using suitable algorithms at different clustering levels. The records within each cluster are then perturbed such that the statistical properties of the clusters remain unchanged.

Abstract: A method of generating an image includes the step of obtaining captured data characterizing an object. The method also includes the step of reconstructing a spatio-temporal image of the object based on the captured data, the spatio-temporal image comprising a plurality of spatial images in respective time intervals, with at least a given one of the spatial images in one of the time intervals being reconstructed using captured data from a frame associated with that time interval and captured data associated with one or more additional frames associated with other time intervals. The method further includes the step of outputting the spatio-temporal image. The obtaining, reconstructing and outputting steps are performed by a processing device comprising a processor coupled to a memory.

Abstract: Impulse noise from nearby or intense electrical sources can disrupt communications over digital subscriber lines (DSL). The characterization of the nature, timing and length of impulse noise sources present on a DSL loop is a critical first step in mitigating the effect of impulse noise on DSL communications. DSL standards provide histograms for impulse length and inter-arrival time of impulses. These histograms can be used to derive the nature, maximum frequency and other statistics related to impulse noise on a DSL line.

Abstract: A spatio-temporal image of an object is reconstructed based on captured data characterizing the object. The spatio-temporal image comprises a plurality of spatial images in respective time intervals, and at least a given one of the spatial images in one of the time intervals is reconstructed using not only captured data from a frame associated with that time interval but also captured data associated with one or more additional frames associated with other time intervals. The spatio-temporal image may be reconstructed by iteratively obtaining a solution to a minimization or maximization problem in a sparse domain and transforming the solution to an image domain. The transformation between the sparse domain and the image domain may utilize a spatio-temporal transformation implemented using a plurality of basis functions, one or more of which may be determined at least in part based on secondary information associated with the imaged object.

Abstract: Systems and methods for modeling functional magnetic resonance image datasets using a multivariate auto-regressive model which captures temporal dynamics in the data, and creates a reduced representation of the dataset representative of functional connectivity of voxels with respect to brain activity. Raw spatio-temporal data is processed using a multivariate auto-regressive model, wherein coefficients in the model with high weights are retained as indices that best describe the full spatio-temporal data. When there are a relatively small number of temporal samples of the data, sparse regression techniques are used to build the model. The model coefficients are used to perform data processing functions such as indexing, prediction, and classification.