116 results about "Temporal context" patented technology

A system to pair advertisements with media files is described. A request is processed to find one or more relevant advertisements and determine when to display each relevant advertisement at a temporally contextual point within a video file when the video file is played on a web page. The video file's key concepts and timing information are retrieved from a database. A request is generated for advertisements that contextually match the content in the key conceptual points found in the content of the video file. The timing information is retrieved regarding when the key conceptual points, relevant to returned advertisements that contextually match, chronologically appear in the video file. Contextual relevant advertisements are supplied with temporal information on when the placement of advertisements is most contextually relevant to the content being played in the video file.

A method and system for presenting a set of graphic images on a television system is presented. A sequence of frames of a video is received. The frames are decoded and scaled to reduced size frames, which are sampled temporally and periodically to provide selected frames. The selected frames are stored in a circular buffer and converted to graphic images. The graphic images are periodically composited and rendered as an output graphic image using a graphic interface.

A method improving scene classification of a sequence of digital images comprising the steps of: (a) providing a sequence of images captured in temporal succession; (b) classifying each of the images individually based on information contained in the image alone to generate a first image classification; and (c) imposing a pre-determined temporal context model on the sequence of images to generate a final image classification for each image in the sequence.

A description of a user is estimated based on the context of a user's past and present locations. A disclosed data-processing system continually receives data points for each user that represent spatial and / or temporal events. These events represent, for example, presence of a person at a specific geographic location such as a geographic area or point of interest (POI). The data-processing system evaluates the received data points in relation to one or more of the geographic locations, yielding results that are also based on the demographic characteristics of each visited location and the commercial characteristics of each visited location. The data-processing system evaluates the data points also to determine patterns exhibited in each user's activity or inactivity, and patterns exhibited in the distance traveled and the type of travel. The data-processing system bases the user descriptions on the results of these evaluations.

Techniques and mechanisms described herein facilitate the performance of time context weighted content recommendation. According to various embodiments, information identifying one or more viewing events or actions detected in association with a designated content management account at a media system may be received. The one or more viewing events or actions may have associated therewith time information indicating a time at which the one or more viewing events or actions occurred. The designated content management account may provide access to a plurality of media content items via the media system. The designated content management account may be associated with a time context viewing profile. The time context viewing profile designating one or more of the plurality of media content items for recommendation in association with the designated content management account. The time context viewing profile may also designate a time context for recommending the designated media content items.

This invention relates to one rapid movement estimation method, which comprises the following steps: a, dividing each frame of images into several blocks and determining vector space upper and down message on each current image composed of upper and down messages to determine several prepare motion vector; computing each prepare motion vector matching error values with low motion matching error values with current pixel module designed as motion vector step.

A voltage analysis algorithm for automatically determining anomalous voltage conditions in an electrical system monitored by a plurality of intelligent electronic devices (IEDs) and automatically making recommendations for ameliorating or eliminating the anomalous voltage conditions. The electrical system hierarchy is determined automatically or manually, and the algorithm receives voltage data from all capable IEDs. The voltage data is temporally aligned or pseudo-aligned to place the voltage data in both spatial and temporal context. The algorithm determines anomalous voltage conditions systemically by comparing measured voltage values against nominal or expected ones across the system. Based on the spatial and temporal context of the IEDs, the algorithm automatically identifies a source of the voltage deviation in the hierarchy, and recommends a modification associated with the source for mitigating the anomalous voltage condition. The algorithm checks its recommendation to determine any adverse effects on the electrical system and adjusts the recommendation accordingly.

A system and method for enabling multithreading in a embedded processor, invoking zero-time context switching in a multithreading environment, scheduling multiple threads to permit numerous hard-real time and non-real time priority levels, fetching data and instructions from multiple memory blocks in a multithreading environment, and enabling a particular thread to modify the multiple states of the multiple threads in the processor core.

Methods and apparatus for performing computer-implemented extraction of temporal information for business entities and events are disclosed. In one embodiment, a sequence of text is obtained. A label is assigned to one or more of a plurality of segments of the text such that each of the one or more of the plurality of segments of the text is classified as temporal data in one of a plurality of classes of temporal data. One or more rules are applied to the one or more segments of the text that have been classified as temporal data to generate a structured representation of the temporal data, where the rules include one or more schematic rules. Each of the schematic rules pertains to one or more of the plurality of classes of temporal data and indicates a structure in which temporal data in the corresponding one or more of the plurality of classes is to be stored.

A method and system to detect and evaluate harmonic distortion in an electrical power system is disclosed. A plurality of monitoring devices is installed in the electrical power system. The hierarchy of the electrical power system is received. Data indicative of harmonic distortion on the electrical power system is received from at least two of the monitoring devices. The data indicative of harmonic distortion is automatically aligned in a temporal or pseudo-temporal context. An electrical characteristic of the harmonic distortion from the data indicative of harmonic distortion is determined.

A method and system to detect and evaluate harmonic distortion in an electrical power system is disclosed. A plurality of monitoring devices is installed in the electrical power system. The hierarchy of the electrical power system is received. Data indicative of harmonic distortion on the electrical power system is received from at least two of said plurality of monitoring devices. The data indicative of harmonic distortion is automatically aligned in a temporal or pseudo-temporal context. An electrical characteristic of the harmonic distortion from the data indicative of harmonic distortion is determined.

The invention discloses a collaborative filtering recommendation method for integrating time contextual information, which is used for integrating the time contextual information on the basis of an original item-based collaborative filtering recommendation algorithm and an original user-based collaborative filtering recommendation algorithm and combining the original item-based collaborative filtering recommendation algorithm and the original user-based collaborative filtering recommendation algorithm into a uniform algorithm. The collaborative filtering recommendation method comprises the steps of for the user-based collaborative filtering recommendation algorithm, firstly, integrating a time attenuation function in a user similarity calculation stage; then, clustering items, and training interest attenuation factors of a user on an article category; finally, integrating the time attenuation function in a rating prediction stage, wherein for the item-based collaborative filtering recommendation algorithm, the process is similar to the process of the user-based collaborative filtering recommendation algorithm, and the two algorithms can be finally combined into the uniform algorithm. According to the collaborative filtering recommendation method disclosed by the invention, the time attenuation function is introduced in both the similarity computation stage and the rating prediction stage, different time attenuation factors are used for different types of items by different users, and thus the prediction accuracy can be effectively increased.

Embodiments of the present invention provide a desktop search tool that allows users to efficiently retrieve or locate a desired object on their computer. Users specify their search based on a time context In addition, the desktop search tool may provide its results in a temporal context to assist the user in browsing through the results.

The invention provides a tracking algorithm based on spatio-temporal context fusion multi-feature and scale filtering. Target position information and size information of a first frame of image are obtained through a video or image sequence; parameter initialization is performed; multi-feature extraction is performed; double-step preprocessing operation is performed, and operation of the cosine window is performed in a feature target area so that the edge effect caused by Fourier transform can be reduced; a filtering template and a scale filtering template are obtained through two times of Fourier transform; a position filtering template and the scale filtering template under the time domain space are obtained through two times of inverse Fourier transform, and the corresponding maximum value, i.e. the target area, is solved; finally the position filtering model, the scale filtering model, an adaptive appearance model and spatio-temporal context information are updated through a new frame; and the process returns to the feature extraction part and target tracking is performed through cyclic operation until the end of the process. According to the method, the tracking accuracy can be enhanced, the appearance change and the scale change of the target in the tracking process can be better adapted and the noise caused by the change of the environment in the tracking process can bereduced.

The embodiments of the present system includes a mobile device with a native or installed mobile application that communicates with a cloud platform for context based content delivery to the mobile terminal device. The mobile cloud platform includes a mobile cloud virtualization layer, a mobile cloud content delivery layer and a mobile cloud network layer. The mobile cloud virtualization layer functions as a storage and process center. It allocates resources for native applications and other user information storage, content storage for static services, content storage for dynamic services and runs application processes for mobile users independent of the mobile platform. The mobile cloud content delivery layer runs a context-adaptive engine that delivers service provider content to a mobile platform based on space-time context of the user. The mobile cloud network layer forms dynamic local networks as well as high frequency usage networks with other mobile terminal devices based on the user analytical data.

Embodiments of the present invention provide a desktop search tool that allows users to efficiently retrieve or locate a desired object on their computer. Users specify their search based on a time context. In addition, the desktop search tool may provide its results in a temporal context to assist the user in browsing through the results.

The invention discloses a method and device for determining a point of interest, a storage medium and an electronic device. The method includes the following steps: obtaining a first positioning request, wherein the first positioning request is used to request to acquire a target point of interest where a target account is located; searching for candidate points of interest corresponding to location information of the target account in response to the first positioning request; and selecting the target point of interest matching spatial context features and temporal context features of the target account from the candidate points of interest, wherein the spatial context features are used to represent a spatial correlation relationship between the points of interest, and the temporal context features are used to represent a temporal correlation relationship between the points of interest. According to the scheme of the invention, the technical problem that the accuracy of positioning the point of interest (POI) of the user is relatively low in related technologies can be solved.

During operation, a computer may monitor values of at least one performance metric associated with packet communication by access points in a network. Then, the computer may compare current values of the performance metric for the access points with historical values of the performance metric for the access points within a temporal context in order to determine temporal anomaly scores for the access points. Moreover, the computer may compare the temporal anomaly scores of a group of access points in order to determine spatial temporal anomaly scores for the access points that indicate a significance of the temporal anomaly scores in a spatial context. Furthermore, when a spatial temporal anomaly score for an access point meets a detection criterion, the computer system may identify the current value of the performance metric for the access point as an anomaly. Next, the computer system may perform a remedial action based on the identified anomaly.

Methods and apparatus related to context management in a networked environment are provided. According to one aspect, a technique is provided for facilitating communication between a client and a context management (CM) server, comprising establishing a network connection between the client and the CM server to enable communication, and maintaining the connection for the period of time during which the context is maintained.

The invention relates to the technical field of speech processing and specifically provides a method and a device for estimating a noise power spectral density of a speech signal. The method comprisesthe following steps: extracting a time context window feature from a noise speech signal, inputting the time context window feature to a pre-trained speech existence probability estimator which outputs an estimated speech existence probability corresponding to a current time frame; correcting the estimated speech existence probability according to a Bayes rule to determine a speech existence probability; determining the noise power spectral density corresponding to the corresponding time frame based on the speech existence probability according to a recursive smoothing formula. Through the technical scheme of the invention, the estimation accuracy of the noise power spectral density is improved in the case of small computing resources, thereby being beneficial to effectively eliminating noise signals, minimizing distortion in the speech processing process and improving speech enhancement performance.

A system and a method for time series forecasting. The method includes: providing input feature vectors corresponding to a plurality of future time steps; performing bi-directional long-short term memory network (BiLSTM) on the input feature vectors to obtain hidden outputs corresponding to the plurality of future time steps; for each future time step: performing temporal convolution on the hidden outputs using a plurality of temporal scales to obtain context features at the plurality of temporal scales, and summating the context features at the plurality of temporal scales using a plurality of weights to obtain multi-scale context features; and converting the multi-scale context features to obtain the time series forecasting corresponding to the future time steps.

A method including receiving an image sequence, wherein the image sequence includes a plurality of two-dimensional (2D) image frames of an organ arranged in a time sequence; constructing a three-dimensional (3D) volume by stacking a plurality of the 2D image frames in time order; detecting a best bounding box for a target of interest in the 3D volume, wherein the best bounding box is specified by a plurality of parameters including spatial and temporal information contained in the 3D volume; and determining the target of interest from the best bounding box.

A system and method for providing an adaptive experience framework for an ambient intelligent environment are disclosed. A particular embodiment includes: detecting as context change in an environment causing a transition to a current temporal context; assigning, by use of is data processor, as task set from a set of contextual tasks, the task set assignment being based on the current temporal context; activating the task set; and dispatching a set or interaction resources, corresponding to the contextual tasks in the task set, to present a state of the current temporal context to a user by use of a plurality of interaction devices corresponding to the set of interaction resources.

Embodiments of the present invention provide a desktop search tool that allows users to efficiently retrieve or locate a desired object on their computer. Users specify their search based on a time context. In addition, the desktop search tool may provide its results in a temporal context to assist the user in browsing through the results.

The invention relates to a pedestrian re-identification and tracking method based on spatio-temporal context, which comprises the following steps: training a Mask RCNN network; Using the trained MaskRCNN network to process the original picture set, the training set, the test set and the search set. Training convolution neural network with training set; The test set and the search set are processed using the trained convolution neural network to obtain a first preset number of pictures from the test set for reidentifying the target pedestrian. The invention uses the object detection algorithmand the instance segmentation algorithm to preprocess the picture, removes the background interference information, further improves the model precision, and improves the accuracy of the pedestrian re-identification method. At that same time, the invention solve the problem that the current pedestrian re-identification algorithm lacks the tracking function, and proposes the area prediction algorithm based on the walking speed, and combine the Mask RCNN to reduce the tracking calculation complexity, achieve real-time tracking, and improve the tracking efficiency.

The invention discloses a bipartite graph recommendation method based on a key user and a time context, which belongs to the technical field of personalized intelligent recommendation. The method comprises steps of acquisition of feedback data of a user to a goods, extraction of a key user collection, building of an interest preference neighbor collection of the user, material resource diffusion on a cut user-goods bipartite graph and final recommendation. By adopting the method, the key user group that plays a leading role in the recommendation system is mined, an interest nearest neighbor collection C for the target user is found out in the group, the bipartite graph is cut according to the collection C, nodes and edges in no relation or weak relation with the target user are removed, the calculation complexity is thus reduced, and the real-time performance of the recommendation algorithm is ensured. Besides, during the material diffusion process in the second step, a user score timedecay function is introduced, the different contribution degrees of different time scores to the recommendation results are reflected, and the algorithm recommendation accuracy is thus improved.

The invention discloses a video target detection method based on deep learning, and is applied to the field of video target detection. According to the method, the convolutional neural network is usedfor extracting image features, and time-is provided; And the spatial feature extraction network is used for extracting spatial context and time context information of the video, fusing image featureswith time and spatial context information, updating a feature map output by the backbone network, and finally inputting the obtained feature map into the detection network to obtain a final detectionresult, thereby giving consideration to the accuracy and real-time performance of target detection. According to the method, the detection accuracy and real-time performance are effectively improved.

The invention relates to the technical field of computer vision processing, and discloses a real time human face tracking method and a system based on spatio-temporal context learning. The method specifically comprises the following steps: Step 1, initial frame human face detecting and target human face determining; obtaining positions of all the human faces in an initial frame through a human face detector and transmitting determined target human face positions to a tracker to begin tracking; Step 2, historical frame information learning and module updating; Step 3, present frame candidate target human face determining; and Step 4, present frame target position determining: from the second frame, for the n frame (n>1), a candidate target human face is mixed with an updated tracking result to obtain the final position of the human face in the present frame. The tracker and an effect determining device are updated through the above method so as to enable effective combination of the tracking and the human face detection result in a framework of learning. The tracking is enabled to be adapted to problems facing long-time tracking. Simultaneously, problems of tracking drift or failures due to interference human faces are solved.