561 results about "Event recognition" patented technology

Systems and methods for processing contact information are described. In one embodiment, an entity name is identified from an event associated with an article, wherein the entity name is associated with an entity and the event is associated with a user, contact information associated with the entity name is identified, the entity name and at least some of the contact information is indexed, and the entity name and at least some of the contact information is stored.

Enables recognition of events within motion data including but not limited to motion capture data obtained from portable wireless motion capture elements such as visual markers and sensors, radio frequency identification tags and motion sensors within mobile device computer systems, or calculated based on analyzed movement associated with the same user, other user, historical user or group of users. Provides low power transmission of events. Greatly reduces storage for events such as a shot, move or swing of a player, a concussion of a player, boxer, rider or driver, or a heat stroke, hypothermia, seizure, asthma attack, epileptic attack. Events may be correlated with image(s) as captured from internal / external camera(s) or nanny cam, for example to enable saving video of the event, such as the first steps of a child, violent shaking events, sporting, military or other motion events including concussions, or falling events associated with an elderly person.

A method, system, and computer program product for associating events. A provided event dataset includes events occurring in each of N successive time intervals (N≧3). Association rules pertaining to successive events in the event dataset are deduced. Sequences of events are generated from the association rules. Clusters of the sequences of events are formed. Sequences of the clusters are created. The clusters of the sequences may be used: to identify at least one event occurring in a time interval of the N time intervals as being a probable cause of at least one event occurring in a later-occurring time interval of the N time intervals; or to predict an occurrence of at least one event in a time interval occurring after the N time intervals, wherein the at least one event had occurred within the N time intervals.

Enables event analysis from sensors including environmental, physiological and motion capture sensors. Also enables displaying information based on events recognized using sensor data associated with a user, piece of equipment or based on previous motion analysis data from the user or other user(s) or other sensors. Enables intelligent analysis, synchronization, and transfer of generally concise event videos synchronized with motion data from motion capture sensor(s) coupled with a user or piece of equipment. Enables creating, transferring, obtaining, and storing concise event videos generally without non-event video. Events stored in the database identifies trends, correlations, models, and patterns in event data. Greatly saves storage and increases upload speed by uploading event videos and avoiding upload of non-pertinent portions of large videos. Creates highlight and fail reels filtered by metrics and can sort by metric. Compares motion trajectories of users and objects to optimally efficient trajectories, and to desired trajectories.

Video and corresponding metadata is accessed. Events of interest within the video are identified based on the corresponding metadata, and best scenes are identified based on the identified events of interest. A video summary can be generated including one or more of the identified best scenes. The video summary can be generated using a video summary template with slots corresponding to video clips selected from among sets of candidate video clips. Best scenes can also be identified by receiving an indication of an event of interest within video from a user during the capture of the video. Metadata patterns representing activities identified within video clips can be identified within other videos, which can subsequently be associated with the identified activities.

A system that analyzes data from sensors and video cameras to generated synchronized event videos and to automatically select or generate tags for an event. Enables creating, transferring, obtaining, and storing concise event videos generally without non-event video. Events stored in the database identifies trends, correlations, models, and patterns in event data. Tags may represent for example activity types, players, performance levels, or scoring results. The system may analyze social media postings to confirm or augment event tags. Users may filter and analyze saved events based on the assigned tags. The system may create highlight and fail reels filtered by metrics and by tags.

Systems, methods, and manufactures for a surveillance system are provided. The surveillance system includes sensors having at least one non-overlapping field of view. The surveillance system is operable to track a target in an environment using the sensors. The surveillance system is also operable to extract information from images of the target provided by the sensors. The surveillance system is further operable to determine probablistic confidences corresponding to the information extracted from images of the target. The confidences include at least one confidence corresponding to at least one primitive event. Additionally, the surveillance system is operable to determine grounded formulae by instantiating predefined rules using the confidences. Further, the surveillance system is operable to infer a complex event corresponding to the target using the grounded formulae. Moreover, the surveillance system is operable to provide an output describing the complex event.

An apparatus and method for providing a user interface for interacting to various touch events detected by multiple touch sensors formed on the different surfaces of a mobile terminal are provided. The method, for a mobile terminal having a first touch area and a second touch area, includes detecting a touch event that includes a first touch sensed on the first touch area and a second touch sensed on the second touch area, identifying a movement pattern of the touch event, and providing a user interface in accordance with the movement pattern. The apparatus and method for providing a user interface according to the present invention is advantageous to input various user commands intuitively using multi-touch gestures and improve utilization of the mobile terminal with enriched emotional expressions.

Disclosed is a lane changing and overtaking assisting method and system based on inter-vehicle communication. The method is characterized in that inter-vehicle communication is built among different vehicles, information support is provided for lane changing and overtaking is provided for drivers of the vehicles through information interaction, the inter-vehicle communication is achieved through short-range communication protocols, when a driver triggers a lane changing and overtaking event, a system identify and process the event and transmits the same to a specified vehicle, and the vehicle received the event restores the event and displays the same as prompt information which can be identified by the driver of the specific vehicle. The system comprises an event identifying module, an event processing module, a wireless communication transceiving module, an event restoring module, a user interface module, and a hardware system formed by a wireless communication device, a positioning device, an antenna, an information processing system and a touch screen. By the method and the system which can be normally used under conditions of bad weather and bad vision, driving safety can be increased effectively.

Enables recognition of events within motion data including but not limited to motion capture data obtained from portable wireless motion capture elements such as visual markers and sensors, radio frequency identification tags and motion sensors within mobile device computer systems, or calculated based on analyzed movement associated with the same user, other user, historical user or group of users. Provides low power transmission of events. Greatly reduces storage for events such as a shot, move or swing of a player, a concussion of a player, boxer, rider or driver, or a heat stroke, hypothermia, seizure, asthma attack, epileptic attack. Events may be correlated with image(s) as captured from internal / external camera(s) or nanny cam, for example to enable saving video of the event, such as the first steps of a child, violent shaking events, sporting, military or other motion events including concussions, or falling events associated with an elderly person.

A method, system, apparatus, or computer program product is presented for morphing a honeypot system on a dynamic and configurable basis. The morphing honeypot emulates a variety of services while falsely presenting information about potential vulnerabilities within the system that supports the honeypot. The morphing honeypot has the ability to dynamically change its personality or displayed characteristics using a variety of algorithms and a database of known operating system and service vulnerabilities. The morphing honeypot's personality can be changed on a timed or scheduled basis, on the basis of activity that is generated by the presented honeypot personality, or on some other basis. The morphing honeypot can also be integrated with intrusion detection systems and other types of computer security incident recognition systems to correlate its personality with detected nefarious activities.

Described are techniques used in a wire diagnostics system to detect events, such as defects, that may occur within a wire or cable under test. An incident voltage signal is sent out on the wire and a measured voltage signal is obtained which includes the incident voltage and the reflected voltage. Compensation processing is performed on the measured waveform to remove unwanted reflective components. Additionally, the waveform is then subject to attenuation processing and event detection processing. Detected events, such as defects, are classified and output as results. Events are classified by parametric classification using a library of known events or faults. The library of known events or faults is previously generated using empirical analysis and modeling techniques. Additionally, joint time-frequency domain reflectometry (TFDR) techniques are described for event identification and classification for a wire under test.

A computer-implemented method and system is operable to: receive a tracking event from a client, recognize tracking specific parameters in the tracking event, generate a tracking entry corresponding to the tracking event, use a tracking service API to send the tracking entry to a second server, and redirect the client to an intended target corresponding to the tracking event.

A method and system for automatic signalling an alert when a possible intrusion occurs in an industrial automation and control system, based on security events which occur in the industrial automation and control system or are externally fed into the system. The method includes the steps of: (a) determining a correlation of a first and second security event and storing the correlation in an event database, wherein the correlation includes a probability that the first security event is followed by the second security event within a normalised time period, (b) identifying a candidate event as the first security event, based on event information of the candidate event, upon occurrence of the candidate event, (c) classifying the candidate event as anomalous when the probability exceeds a predetermined threshold and no second security event follows the candidate event within the normalised time period, and (d) signalling the alert indicating the candidate event.

Video and corresponding metadata is accessed. Events of interest within the video are identified based on the corresponding metadata, and best scenes are identified based on the identified events of interest. In one example, best scenes are identified based on the motion values associated with frames or portions of a frame of a video. Motion values are determined for each frame and portions of the video including frames with the most motion are identified as best scenes. Best scenes may also be identified based on the motion profile of a video. The motion profile of a video is a measure of global or local motion within frames throughout the video. For example, best scenes are identified from portion of the video including steady global motion. A video summary can be generated including one or more of the identified best scenes.

The invention relates to a dispatching management system and a method for event emergency response of urban bus passenger transport. Methods of combining actual measurement data, event prediction model and algorithm as well as event real-time dispatching model and algorithm are comprehensively applied; geographical information technology, locating technology and modern communication technology are scientifically integrated; bus emergency dispatching technology developed through bus network intellectualization and multi-way coordinative dispatching technology of an urban bus passenger transport system are utilized; and an emergency coordinative dispatching model and the method are established by taking the networked bus passenger transport vehicle dispatching and operation dispatching management as a core and based on the key theories and methods for multi-way and multi-line intelligent coordinative dispatching of a urban bus and passenger transport system. The invention provides excellent theory, methods and technique supports for the real-time dispatching of urban bus events, effectively reduces the event recognition time, generates a quick real-time dispatching strategy, effectively eliminates the influences generated by the events, and resumes the driving plan so as to effectively improve the running efficiency and safety of buses.

A method and apparatus for the incorporation of additional processor generated events. The processor generally comprises a storage area, an indication unit, and a retriever. The storage area stores an indication. Upon recognition of each event, the indication unit alters the state of the indication-i.e., if an event is generated by the processor, the indication unit alters the state of the indication to a first state; and if an event is not generated by the processor, the indication unit alters the state of the indication to a second state. The retriever retrieves, in response to delivery of either a first processor generated event or a second non-processor generated event, a pointer which identifies a corresponding selector. This selector causes the processor to execute either a first number of instructions corresponding to the processor generated event or a second number of instructions corresponding to the non-processor generated event based on the indication.

Methods, systems and products are provided relevant alert delivery including assigning by an event analyzer each received event to an events pool; determining by the event analyzer in dependence upon event analysis rules and the events assigned to the events pool whether to suppress one or more of the events; identifying by the event analyzer in dependence upon event analysis rules and the events assigned to the events pool one or more alerts; sending by the event analyzer to an alert analyzer all the alerts identified by the event analyzer; assigning by the alert analyzer the identified alerts to an alerts pool; determining by the alert analyzer in dependence upon alert analysis rules and the alerts in the alert pool whether to suppress any alerts; and transmitting the unsuppressed alerts to one or more components of the distributed processing system.

Methods, systems, and computer program products for event management in a distributed processing system are provided. Embodiments include receiving, by the incident analyzer, one or more events from one or more resources, each event identifying a location of the resource producing the event; identifying, by the incident analyzer, an action in dependence upon the one or more events and the location of the one or more resources producing the one or more events; identifying, by the incident analyzer, a location scope for the action in dependence upon the one or more events; and executing, by the incident analyzer, the identified action.

Techniques for generating a storyboard are disclosed. In one embodiment of the invention the storyboard is comprised of videos from one or more cameras based on the identification of activity in the video. Various embodiments of the invention include an assessment of the importance of the activity, the creation of a storyboard presentation based on importance and interaction techniques for seeing more details or alternate views of the video. In one embodiment, motion detection is used to determine activity in one or more synchronized video streams. Periods of activity are recognized and assigned importance assessments based on the activity, important locations in the video streams, and events from other sensors. In different embodiments, the interface consists of a storyboard and a map.

Described are techniques used in a wire diagnostics system to detect events, such as defects, that may occur within a wire or cable under test. An incident voltage signal is sent out on the wire and a measured voltage signal is obtained which includes the incident voltage and the reflected voltage. Compensation processing is performed on the measured waveform to remove unwanted reflective components. Additionally, the waveform is then subject to attenuation processing and event detection processing. Detected events, such as defects, are classified and output as results. Events are classified by parametric classification using a library of known events or faults. The library of known events or faults is previously generated using empirical analysis and modeling techniques. Additionally, joint time-frequency domain reflectometry (TFDR) techniques are described for event identification and classification for a wire under test.

Techniques for providing event driven notifications are disclosed. In one particular exemplary embodiment, the techniques may be realized as a method for providing event driven notifications comprising monitoring an electronic media feed for an event associated with a specified criteria, identifying, using at least one computer processor, a plurality of events in the electronic media feed, filtering the plurality of events, identifying an event of the plurality of events matching a specified location, and providing a notification associated with the identified event.

Disclosed are systems and methods for improving image recognition by using information from sensor data. In one embodiment, the method comprises receiving one or more sensor records, the sensor records representing timestamped sensor data collected by a sensor recording device; selecting an event based on the sensor records; identifying a time associated with the event; retrieving a plurality of timestamped video frames; synchronizing the sensor records and the video frames, wherein synchronizing the sensor records and the video frames comprises synchronizing the timestamped sensor data with individual frames of the timestamped video frames according to a common timeframe; and selecting a subset of video frames from the plurality of timestamped video frames based on the selected event.

A method, system, and computer program product for associating events. A provided event dataset includes events occurring in each of N successive time intervals (N≧3). Association rules pertaining to successive events in the event dataset are deduced. Sequences of events are generated from the association rules. Clusters of the sequences of events are formed. Sequences of the clusters are created. The clusters of the sequences may be used: to identify at least one event occurring in a time interval of the N time intervals as being a probable cause of at least one event occurring in a later-occurring time interval of the N time intervals; or to predict an occurrence of at least one event in a time interval occurring after the N time intervals, wherein the at least one event had occurred within the N time intervals.

The invention discloses an analysis method, apparatus and system for user water bath behavioral habits. The method comprises following steps: acquiring user history using data of a water heater, wherein the user history using data includes water flow information and using time information; acquiring a water using event according to the water flow information and using time information; determining whether the water using event is a continuous water bath event according to continuous bath event recognition rules; dividing the continuous water bath event into multiple individual water bath cases if the water using event is the continuous water bath event; recognizing bath cases among the multiple individual water bath cases and acquiring water bath behavior information corresponding to the bath cases; and generating corresponding user water bath behavioral habit data according to the water bath behavior information corresponding to the bath cases. The analysis method for user water bath behavioral habits which is provided by the embodiment of the invention can provide relatively accurate water bath behavioral habit data for users.

The invention relates to a deep-convolution-neural-network-based method for detecting illegal parking and converse running of vehicles. A mobile terminal detection point is used as a road camera. The mobile terminal detection point obtains image information by the camera and depth learning is introduced into road event identification and improvement is also carried out, so that the accuracy of road event identification can be improved obviously. According to the method provided by the invention, a convolution neural network is used for analyzing an obtained image; a pavement ROI region is divided into a plurality of networks; a pavement-non-pavement identification model is constructed; and reverse identification of illegal parking and converse running of vehicles at highways is realized by using a non-pavement grid. The method is applied to non-real-time tasks like pavement illegal parking detection and converse running detection of vehicles. With full utilization of advantages and characteristics of the mobile internet network, high-coverage pavement event detection including illegal parking and converse running of vehicles is realized with low cost.

The invention provides a micro seismic event recognition method based on morphological filtering. The method comprises the steps of conducting spectral analysis on micro seismic data; rectifying a demodulator used for receiving micro seismic signals; selecting structural elements, combining opening operation and closing operation to form a morphological noise filter, and conducting the morphological filtering on the micro seismic data going through spectral analysis; calculating the energy ratio of a long-time window and a short-time window according to the data going through the morphological filtering, and comparing the energy ratio and triggering threshold to identify whether the demodulator has micro seismic events; and conducting microseism pickup according to the micro seismic events. According to the method, the signal to noise ratio of the data can be improved through preprocessing and further filtering treatment; the micro seismic events can be detected quickly and accurately by utilization of the energy ratio method, the fluctuation type of the micro seismic events can be identified through polarization analysis, and first arrival can be picked up accurately by utilization of self-adaptation threshold and the long-time and short-time window energy ratio method.

The invention discloses a method for detecting, tracking and identifying an object abandoning / stealing event, which comprises the following steps of: 1) the detection of a moving object, namely, establishing an adaptive background model, extracting the moving object by utilizing a background difference and performing morphological processing and shadow processing to obtain a more complete and more accurate state of the moving object; 2) the tracking of the moving object, namely, realizing the inter-frame matching of the moving object through a recursion process of estimating, observing and correcting the state of the moving object, and tracking a moving track of the moving object; and 3) event identification, namely, giving a clear definition to the object abandoning / stealing event, judging the occurrence of the event according to the characteristics and the moving track of the moving object, if the event occurs, distinguishing an object abandoning event from an object stealing event, capturing evidence pictures for the identified abandoning and stealing events and giving an audible alarm.