560 results about "Event recognition" patented technology

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.

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.

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 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.

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, 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.

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.

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 a road surface abandoned object detection method based on a deep convolutional network. Mobile terminal detection points serve as road cameras and acquire image information through cameras, and deep learning is introduced into road surface event recognition and is improved so as to significantly improve road event recognition accuracy. According to the method, acquired images are analyzed through the convolutional neural network, and target detection with mobile cameras and static images is achieved; a road surface ROI is divided into multiple meshes, a road surface-non-road surface recognition model is built, and static targets such as highway surface abandoned objects and thrown objects are reversely recognized through non-road surface meshes. The method is applied to non-real-time tasks like detection of road surface abandoned objects and thrown objects, the characteristics and advantages of the mobile internet are fully utilized, and detection of road surface events like road surface abandoned objects with a high region coverage rate is achieved at a low cost.