336 results about "Behavioural analysis" patented technology

A system and method for analyzing and evaluating the performance and attitude of a motor vehicle driver. A raw data stream from a set of vehicle sensors is filtered to eliminate extraneous noise, and then parsed to convert the stream into a string of driving event primitives. The string of driving events is then processed by a pattern-recognition system to derive a sequence of higher-level driving maneuvers. Driving maneuvers include such familiar procedures as lane changing, passing, and turn and brake. Driving events and maneuvers are quantified by parameters developed from the sensor data. The parameters and timing of the maneuvers can be analyzed to determine skill and attitude factors for evaluating the driver's abilities and safety ratings. The rendering of the data into common driving-related concepts allows more accurate and meaningful analysis and evaluation than is possible with ordinary statistical threshold-based analysis.

A baseline can be defined using specific attributes of the network traffic. Using the established baseline, deviation can then be measured to detect anomaly on the network. The accuracy of the baseline is the most important criterion of any effective network anomaly detection technique. In a local area network (LAN) environment, the attributes change very frequently by many change agents; for example, new entities, such as users, application, and network-enabled devices, added to and removed from the LAN environment. The invention provides an improved method of establishing a baseline for network anomaly detection based on user's behaviour profiling. A user behaviour profiling is a distinct network usage pattern pertaining to a specific individual user operating on the LAN environment. No two users profiling would be the same. A group of users that have similar network usage attributes can be extrapolated using data mining technique to establish a group profiling baseline to detect network usage anomaly. By combining user and group profiling, a network anomaly detection system can measure subtle shift in network usage and as a result separate good user's network usage behaviour from the bad one. Using the said technique, a lower rate of false positives of network anomaly can be created that is suitable to operate in a highly dynamic LAN environment.

The present invention relates to a system for the 3-D monitoring and analysis of motion-related behavior of test subjects. The system comprises an actual camera, at least one virtual camera, a computer connected to the actual camera and the computer is preferably installed with software capable of capturing the stereo images associated with the 3-D motion-related behavior of test subjects as well as processing these acquired image frames for the 3-D motion parameters of the subjects. The system of the invention comprises hardware components as well as software components. The hardware components preferably comprise a hardware setup or configuration, a hardware-based noise elimination component, an automatic calibration device component, and a lab animal container component. The software components preferably comprise a software-based noise elimination component, a basic calibration component, an extended calibration component, a linear epipolar structure derivation component, a non-linear epipolar structure derivation component, an image segmentation component, an image correspondence detection component, a 3-D motion tracking component, a software-based target identification and tagging component, a 3-D reconstruction component, and a data post-processing component In a particularly preferred embodiment, the actual camera is a digital video camera, the virtual camera is the reflection of the actual camera in a planar reflective mirror. Therefore, the preferred system is a catadioptric stereo computer vision system.

In the present invention, an apparatus for behavior analysis and method thereof is provided. In this apparatus, each behavior is analyzed and has its corresponding posture sequence through a triangulation-based method of triangulating the different triangle meshes. The two important posture features, the skeleton feature and the centroid context, are extracted and complementary to each other. The outstanding ability of posture classification can generate a set of key postures for coding a behavior sequence to a set of symbols. Then, based on the string representation, a novel string matching scheme is proposed to analyze different human behaviors even though they have different scaling changes. The proposed method of the present invention has been proved robust, accurate, and powerful especially in human behavior analysis.

A method is described for modeling heterogeneous material properties within a geometric model of an object (e.g., within a CAD model). Material functions are defined about material features (i.e., points, surfaces, or areas on or in the model) at which material properties are known, with the material functions each defining the behavior of that feature's material property at locations away from that feature. Combination of the material functions results in a single material function which defines the material properties throughout the geometric model. The resulting material function may then be used in subsequent analyses, such as in computerized behavior analysis of the geometric model. The material function may be constructed such that it meets desired constraints, and has desired smoothness and analytical properties, for ease of use in such subsequent analyses.

The invention discloses a driving behavior analysis method and a driving behavior analysis system. The driving behavior analysis method comprises the following steps: collecting all bad driving behavior data of a driver when the driver drives; uploading the bad driving behaviors data to a data analysis center through networks; multiplying times of various bad driving behaviors and corresponding weight coefficients of bad driving behaviors in the data analysis center to obtain a corresponding weight value; obtaining an assessed value by subtracting the sum of all weight values of bad driving behaviors during a driving from a preset full score of good behaviors. The driving behavior is good if the percentage of the assessed value and the full score value is greater than or equal to X, is general if the percent is greater than or equal to Y and less than X, and is bad if the percent is greater than or equal to Z and less than Y and fails if the percent is less than Z. The analysis method and the analysis system of the driving behaviors can be used for comprehensively, scientifically and accurately assessing bad driving behaviors of a driver and warning the driver in time and meanwhile a company can manage drivers conveniently.

The embodiment of the invention provides a modeling method of an early warning model of mixed failures and a modeling system. The modeling method provided by the invention comprises the following steps of: generating a function analyzing module on the basis of HAZOP (Hazard and Operability Analysis) or FMEA (Failure Mode and Effects Analysis); generating a degeneration analyzing module on the basis of FMEA analyzing results and a theory of stochastic processes; generating an accident analyzing module according to state monitoring data and maintenance action information; generating an action analyzing module according to output results of the function analyzing module and the degeneration analyzing module through combining a DBN (Dynamic Bayesian Network) theory; taking the output of the accident analyzing module as an inference evidence and utilizing a DBN inference algorithm to process forward and backward inferences in the same time period to generate an evaluating module for outputting factors and consequences of system failures; taking the output results of the evaluating module and the accident analyzing module as the inference evidence and utilizing the DBN inference algorithm to process forward and backward inferences in the different time periods to generate a predicating module for outputting prospective degeneration tendencies of each member of the system. The model provided by the invention can be used for tracking the failure factors of the system and inferring possible failure consequences and probability.

With the widespread adoption of SIP-based VoIP, understanding the characteristics of SIP traffic behavior is critical to problem diagnosis and security protection of VoIP services. A general methodology is provided for profiling SIP-based VoIP traffic behavior at several levels: SIP server host, server entity (e.g., registrar and call proxy) and individual user levels. Using SIP traffic traces captured in a production VoIP network, the characteristics of SIP-based VoIP traffic behavior in an operational environment is illustrated and the effectiveness of the general profiling methodology is demonstrated. In particular, the profiling methodology identifies anomalies due to performance problems and/or implementation flaws through a case study. The efficacy of the methodology in detecting potential VoIP attacks is also demonstrated through a test bed experimentation.

The invention discloses an intelligent video monitoring system with privacy protection. The system comprises one or more intelligent video monitoring equipment modules, an IVSS platform server, and a video monitoring system terminal, wherein the intelligent video monitoring equipment modules can realize the intelligent and automation treatments of targets in a monitoring scene such as real-time detection, tracking, classification, behavior analysis and the like, and also realize performing scrambling treatment on contents related to the privacy so as to protect privacy information. According to the technical scheme provided by the invention, the intelligent monitoring method realizing privacy protection can automatically differentiate 'abnormities' in pictures, performs the detection, tracking, classification and behavior analysis on the moving targets, realizes the intelligent alarm, effectively avoids the occurrence of accidents, and can protect the monitored privacy information, and any privacy information is inaccessible to an authorized user.

The invention discloses a driving behavior analyzing and reminding method and system. A data collecting module sends collected driving data to a data processing module, the data processing module preprocesses and sends the data to a wireless communication module, the wireless communication module performs transmission through a transmission module, the data are sent to a remote server through the transmission module, the data are received through a data receiving module, the received data are analyzed and fall into a database, a data analysis module analyzes the uploaded data in real time or analyzes the record of the database to generate a user driving prompt, a monitoring feedback module monitors the analysis result of the automobile data in real time, and when a vehicle-mounted terminal receives the early warning result through the transmission module, an early warning and reminding module can send the prompt to a user. The driving behavior of a driver is recognized and preestimated by analyzing internal automobile body data and external road condition data in the automobile driving process, the bad driving behavior of the driver can be assessed more comprehensively and accurately, and the driver is reminded in time.

The invention discloses a personal driving behaviour analysis management control system, comprising a data reading terminal, a GPS (global positioning system) positing device and a server, wherein the data reading terminal is used for acquiring vehicle ECU (electronic control unit) operational data, reading automobile travelling working condition data, creating a driver operation behaviour data evaluation analysis model, giving an alarm when finding a dangerous driving behaviour, emergently recording vehicle accident data, carrying out statistic on automobile travelling mileage and fuel consumption and detecting whether vehicle emission exceeds the standard or not; the GPS positioning device is used for vehicle positioning; and the server is used for recording and analyzing driving behaviour data, timely reminding a vehicle maintenance fault by combining OBD (on-board diagnostics) vehicle diagnostic function and exchanging information with a user by virtue of an interconnection platform. The invention extracts safety and economy conditions of a vehicle owner by virtue of multiple behaviour models, provides guiding suggestions and ideas for a vehicle owner and alarms and suggests in the automobile driving process and on an Internet terminal interface, thus the system improves driving behaviour and achieves energy conversation and emission reduction, is safety in control, is economic and environment-friendly.

The invention discloses a system and a method for analyzing customer behavior characteristics based on a speech recognition technique. The method comprises the steps that a recording file acquisition engine extracts customer service recoding files from a recording system in a call center at regular time or in real time; a speech recognition module converts the recoding files extracted by the recording file acquisition engine into text files; and a customer behavior analysis module calls a search engine function, analyzes and mines the customer behavior characteristics of an information base in combination with pre-customized rules stored in a semantics rule customization module, and generates information related to customer and/or customer service behavior characteristics. The system and the method for analyzing the customer behavior characteristics are based on the speech recognition technique. Idle audio recording files in the call center are converted into commercial messages with high added value. By providing effective root cause analysis to the performance of the call center, solutions to problems are rapidly provided, actions are taken to reduce call volume and therefore the customer satisfaction is improved.

The invention discloses a panorama video intelligent monitoring method, comprising: A. acquiring a scene panorama image and unfolding it; B. performing intelligent analysis on a moving target in the panorama unfolded image. The invention also discloses a panoramic video intelligent monitoring system, a device for intelligent analysis and processing of panoramic images, and a method and device for unfolding panoramic images. By using these methods, systems, devices and devices, it is possible to reduce Installation cost, automatically distinguish "abnormalities" in the screen, and implement moving target detection, tracking, classification and behavior analysis, realize intelligent alarm, effectively prevent incidents from happening, and save manpower and material resources.

The invention relates to a method for implementing realistic game, which comprises the following steps of: (1) establishing a human body skeleton model; (2) establishing a game movement library under an offline state, establishing movement libraries respectively according to game items, and performing multi-frame movement decomposition on a single semantic movement;(3) calibrating a binocular camera to acquire parameters of the binocular camera and polar calibration; (5) background modeling; (6) selecting an interactive characteristic label; (7) foreground partitioning; (8) initializing the information of the characteristic label; (9) detecting human face and skin color; (10) multi-target tracking; (11) completing sparse stereo matching; (12) acquiring a 3D skeleton; and (13) matching with the movements in the offline movement libraries to realize movement recognition, combining single-frame image analytic matching with multi-frame image analytic matching to obtain the semantic movement, transferring the semantic movement to a game executing unit to implement the function of realistic game. Being stronger in interactivity and reality as well as simpler and more convenient in operation, the method of the invention is a game implementation method with low cost and is more suitable for being extensively accepted by general people.

The invention discloses an advanced driver assistance system. The advanced driver assistance system comprises a data collection module, a driver behavior analysis module, an early warning level adjustment module and an early warning module. The data collection module comprises a road information collection module and a driver information collection module, the driver behavior analysis module performs comprehensive assessment on data collected by the data collection module, and the early warning level adjustment module adjusts the early warning level of the early warning module. According to the advanced driver assistance system, the state of a driver is obtained by collecting and analyzing the behaviors and physical signs of the driver, the early warning level of the ADAS is dynamically adjusted in combination with real-time road conditions and weather conditions, and therefore the early warning timeliness of the ADAS can be effectively improved.

The invention provides a target tracking method and system and a staff behavior analyzing method and system. The target tracking method comprises the steps that a camera is used to acquire a video image; a front head classifier, a back head classifier, a left head classifier and a right head classifier are respectively used to detect candidate head targets in the current image; deduplication and screening are carried out on the candidate head targets detected by the classifiers; head targets which does not meet a tracking condition are deleted; and the remaining head targets are respectively tracked. The technical problems of false positives, false negatives, difficulty tracking and high camera erection requirement, which are caused by easily being blocked, difficulty target classification and the like, of a staff detection and tracking method based on face detection, head and shoulder detection or whole body detection are solved. According to the invention, accurate staff track tracking can be carried out based on the head targets; the problem of target restating can be reduced; and staff behavior analyzing can be carried out based on tracking results.

The invention provides a media technology platform system, a data acquisition system and a network content supplying method. The media technology platform system comprises a data acquisition subsystem used for acquiring online behavior data of a terminal user according to unified personal identification of the terminal user; a data storing subsystem used for receiving the online behavior data of the terminal user and storing the preference information of the terminal user obtained according to the online behavior information of the terminal user; and a data driving subsystem used for providing personalized content information for the terminal user according to the preference information of the terminal user. The media technology platform system, the data acquisition system and the network content supplying method propose and realize the data acquisition and the behavior analysis of online activities of individual users based on the environment of telecommunication Internet, thereby obtaining the completion description of behavior characteristics and demand preference of a single user and also providing intelligent advertised product service and personalized information content service for websites on the Internet.

The invention discloses a nursing home old man dangerous act monitoring method. The problems of low old man tracking accuracy, poor behavior analysis effect, frequent behavior recognition algorithm calling, large system load, excessive dependence on device performance of a monitoring effect and the like in the prior art are overcome. The method is characterized in that a monitoring camera, a video capture card, a personal PC machine, a display and an alarm sound box are used to be combined with a contour detection program module, a tracking program module and a behavior recognition program module in the personal PC machine; and the method based on the combination of target tracking and behavior recognition monitors the movement states of old men in a nursing home in daily life and gives an alarm due to the risks and the abnormal behaviors of the old men. The method has the advantages of high monitoring efficiency, high old man behavior recognition degree, low operation cost and good practicability and application prospect.

The invention is suitable for video monitoring technologies and relates to a method and an apparatus for crowd behavior analysis in video monitoring. The method comprises: obtaining a video stream and dividing each frame of image in the video stream into image sub-blocks with different perspective degrees by taking human height as a size reference by row; extracting deep neural network features in the image sub-blocks; classifying and optimizing the deep neural network features, obtaining a corresponding vector feature set, establishing SVR mathematical models of different kernel functions according to the vector feature set, and making statistics on the number of people in crowds with different density; and adopting a camera calibration method for obtaining coordinate vectors of the deep neural network features, comparing displacements of the deep neural network features of the two continuous frames of image sub-blocks, and calculating a moving direction and a moving speed of the crowd according to the displacement. According to the method and the apparatus, the crowd in the video monitoring is tracked and analyzed to obtain feature information, such as the moving speed, the moving direction, the number of people and the like, of the crowd, the feature information and historical data are analyzed and compared, a state of the crowd is judged, and an alarm is given for an abnormal event.

Provided is a multi-target driving behavior evaluation analytical method based on environmental perception information. The environmental perception information inside and outside a vehicle during the vehicle travelling process is collected through a vehicle environmental perception information collection system, obtained multi-source data are fused and analyzed to obtain specific parameters under different working conditions, and driving behaviors of a driver are evaluated in aspects of driving safety, driving legality, driving efficiency and driving handiness. According to the multi-target driving behavior evaluation analytical method, by collecting and fusing the multi-source data, the driving behaviors of the driver are evaluated, and the multi-target driving behavior evaluation analytical method is applied to insurance companies for obtaining the evaluation information of different drivers to conduct insurance assessment of different grades according to the driving behaviors of the specific driver.

The embodiment of the invention discloses a target value area analysis method and device, and apparatus based on big data and a medium. The method comprises the steps of obtaining network operation and maintenance O-domain big data and operation analysis B-domain big data; performing association analysis on the O-domain big data and the B-domain big data, positioning a target value area, and obtaining a target network grid corresponding to the target value area; based on the O-domain big data and the B-domain big data, performing user behavior analysis on the target value area, and constructing a user portrait; constructing a user flow model based on O-domain and B-domain big data; and performing service traffic prediction on the user traffic model based on the target network grid and theuser portrait, rasterizing the predicted service traffic, identifying a target value user from the traffic grid, and performing network planning on the target value area according to the target network grid and the target value user. By utilizing the embodiment of the invention, O-domain and B-domain big data can be integrated, and network planning optimization and marketing can be better supported.

A method, system, computer program product and/or computer readable medium of instructions for detecting if a processing system has been compromised with audio/visual threat. The method comprises steps of intercepting one or more requests to perform an activity associated with an audio and/or visual communication device of the processing system; and performing a behavioural analysis of the processing system to determine if the processing system exhibits behavioural characteristics indicative of the processing system having been compromised with an audio/visual threat.

The present invention discloses analysis system and method of microbubble behavior in biomedicine ultrasonic field based on superhigh speed photograph technology. Specifically, he present invention includes proposing superhigh speed photograph system for observing the microbubbles in ultrasonic field and microscopic superhigh speed photograph system for observing single microbubble; presenting the method of analyzing the microbubble behavior in free field, near tissue and inside microtubule; and presenting the method of controlling microbubbles generation and breaking and estimating microbubble strain.