393 results about "Track analysis" patented technology

A method of targeted advertising includes generating a targeted advertising and / or promotional campaign material corresponding to a client's selections, fulfilling the targeted advertising and / or promotional campaign material, and providing a response tracking analysis to the client. The targeted advertising and / or promotional campaign material includes a response tracking capability. Access for the client to contact a central facility having public and / or private client databases with list management capabilities can be provided on-line via a client web site. The client can choose from a selection of templates to design of the targeted advertising and / or promotional campaign material. Also, the client can choose from a selection of intended recipients by using and / or modifying a new or pre-existing customer list. The targeted advertising and / or promotional campaign material can be manufactured and distributed to the intended recipients. Preferably, the advertising and / or promotional campaign material includes a coupon having a machine readable mark, symbol, or barcode that incorporates information relating to the client, the customer, and the advertising and / or promotional campaign. The scanned coupon can be communicated back to the central facility and the client can be notified by the central facility as to the response characteristics of the advertising and / or promotional campaign. A closed-loop system is also provided that can implement the above targeted advertising method.

The present invention is directed to a system and method for tracking objects, such as customers in a retail environment. The invention is divided into two distinct software subsystems, the Customer Tracking system and the Track Analysis system. The Customer Tracking System tracks individuals through multiple cameras and reports various types of information regarding the tracking function, such as location by time and real world coordinates. The Track Analysis system converts individual tracks to reportable actions. Inputs to the Customer Tracking System are a set of analog or digital cameras that are positioned to view some physical environment. The output of the Customer Tracking System is a set of customer tracks that contain time and position information that describe the path that an individual took through the environment being monitored. The Track Analysis System reads the set of customer tracks produced by the tracking system and interprets the activities of individuals based on user defined regions of interest (ROI). Examples of a region of interest are: (1) a teller station in a bank branch, (2) a check-out lane in a retail store, (3) an aisle in a retail store, and the like.

Certain embodiments of the present invention provide a system and method for distortion analysis and reduction in an electromagnetic tracker. Certain embodiments of the system include a tracking analysis unit for analyzing a tracking behavior of an instrument and a tracking modification unit for compensating for the tracking behavior of the instrument. The tracking modification unit may compensate for the tracking behavior of the instrument by adjusting the tracking behavior of the instrument. The tracking modification unit may also compensate for the tracking behavior of the instrument by adjusting a tracking system for tracking the instrument. The tracking analysis unit may test the adjusted tracking behavior of the instrument. In an embodiment, the tracking analysis unit generates a map and / or a model of a distortion characteristic of the instrument. The distortion characteristic may be a magnetic field. The distortion handling system is a computer simulated distortion handling system.

A method and system for tracing profiling information using per thread metric variables with reused kernel threads is disclosed. In one embodiment kernel thread level metrics are stored by the operating system kernel. A profiler request metric information for the operating system kernel in response to an event. After the kernel thread level metrics are read by the operating system for a profiler, their values are reset to zero by the operating system kernel. The profiler then applies the metric values to base metric values to appropriate Java threads that are stored in nodes in a tree structure base on the type of event and whether or not the kernel thread has been reused. In another embodiment non-zero values of thread level metrics are entered on a liked list. In response to a request from a profiler, the operating system kernel reads each kernel thread's entry in the linked list and zeros each entry. The profiler can then update the intermediate full tree snapshots of profiling information with the collection of non-zero metric variables.

A method and system for tracing the failing or successful execution of nested functions coded with return codes in a thread during its execution. The method comprises an ENTRY and EXIT trace macro to mark the beginning and the end of execution of the function, a TRACE macro to record messages and program variable values, and a QUIT macro marking the failing execution of the corresponding function. Using a Graphical User Interface, an interactive trace analyzer reads the trace file and displays the tree structure of the nested functions and marks, by using different colors, the success or failure of each of them. The trace analyzer utilities help the user to quickly identify the error in the source code corresponding to a function with a failing execution.

The invention provides a system and a method for predicting the coal and gas outburst risk of a mine in real time, which relate to a system and a method for judging mine natural disaster of coal and gas outburst risk degree through combination of artificial intelligence and expert analysis. The system uses a microseismic signal for reflecting the ground stress intensity and the gas outburst quantity for reflecting the gas change as analysis parameters to be combined with the expert experience, and can improve the predicting accuracy of the coal and gas outburst risk to high than 90 percent. The system and the method are characterized in that the system mainly consists of a data collection module, a data transmission module, a real-time data tracking and analysis center and an integrated early warning module, wherein after the data collection module collects underground data, the data is transmitted to the real-time data tracking and analysis center through the data transmission modulefor calculation, analysis and reasoning, and the integrated early warning module gives the early warning when a reasoning result shows that the risk occurs. The invention is applicable to similar mines with the coal and gas outburst risk.

The invention discloses a moving target analyzing and tracking method and system based on video monitoring. The moving target analyzing and tracking method comprises the following steps of: monitoring video acquisition, acquiring video streaming recorded by a monitoring camera; performing image preprocessing: primarily processing an image of the video streaming, and acquiring a processed image; performing target recognition: performing target recognition classification on each foreground object of the processed image, wherein the classified type of targets comprises persons, vehicles and objects; performing motion track analysis: analyzing the motion track of each target according to the setting of an alarm rule, marking a target of which the motion track is matched with the alarm rule as a suspected target, and giving out an alarm; and tracking the target: tracking the suspected target, and recording the actual motion track and the actual motion direction of the suspected target. According to the method, the alarm is automatically given aiming at an abnormal event, the possibility of missing report and error report is reduced, and the workload of security monitoring personnel is lightened.

To provide for management of enterprise environmental programs, the invention is a method, system, and computer program product that performs functions for emissions cataloging, assessing, analyzing, comparing, strategic planning, reporting and viewing. The invention further provides an integrated, modular mechanism with dynamic data promulgation for making strategic performance assessments and investment decisions. The invention uses a plurality of databases and datastores for storing, tracking, analyzing and comparing emissions information, emissions management activity information, market information, regulatory and voluntary compliance information, risk management information, as well as financial, legal, and production information, at an entity, facility, process, and other enterprise levels. The invention further includes a user interactive feature that provides a means for the user of the invention to enter data and receive an analyzed and compared data output display from a central client server.

The invention discloses an Internet video face recognition method based on deep learning, comprising the following steps: (a) marking face data, acquiring an image with a face from the Internet, marking a face location box and the name of the person, and establishing a face image library; and (b) using the face data marked in step (a) to train a convolutional neural network, wherein the input of the convolutional neural network is set as the face location box, and the output of the convolutional neural network is set as a name tag and the confidence level of the name tag. The beneficial effects are as follows: in face track analysis, first, the quality of each face image on the track is evaluated to discard low-quality face images and retain only high-quality images in order to guarantee the reliability of recognition, and then, statistical analysis is made on the tags of face recognition results of single frames on the track, face image quality filtering is carried out, and the face tags of the overall track are decided based on the statistical parameters of the tags, which can effectively avoid the influence of quality of video on the accuracy of recognition.

The invention discloses a video monitoring method and a video monitoring system. The method comprises the following steps: S100, acquiring a video stream to be analyzed currently; S200, detecting whether a motion object exists in the video stream, if yes, carrying out background modeling, morphological process and eliminating shadow, if no, carrying out circular detection; S300, using a particle filtering or a Kalman filtering tracking method to track the motion object; S400, analyzing the shape information and motion characteristics of the motion object, analyzing abnormal situations by utilizing dispersion degree and area information, classifying the motion object and accomplishing abnormal action identification process analysis; and S500, making an emergency alarm when abnormal situation happens to the video stream. With the method in the invention, the motion object can be analyzed intelligently, multiple bottom layer calculation for one same video stream is carried out only once, and miss report and false report rate of abnormal action in monitoring can be reduced; and with the method. Besides, the method also can be linkaged with security, so that monitoring personnel can make response in time.

The invention relates to a human body attitude tracking analysis-based indoor dangerous condition warning method. According to the method, an artificial intelligence network-based human body recognition technology is applied to household appliances such as air conditioners, and therefore, the original monotonous functions of the household appliances can be improved, functions for judging and identifying dangerous behaviors of children which may cause harm, such as moving the household appliances, climbing to high positions and touching sockets, can be increased, and warning can be triggered timely when the dangerous behaviors are detected; functions for judging and identifying the accidental tumble or specific help-seek gestures of old people at home can be increased, and warning can be triggered timely; and whether dangerous conditions such as a fire, occur in a house can be judged, when the dangerous conditions are detected, warning can be triggered timely.

The invention discloses a fake-licensed car recognition method and system based on Hadoop. The method includes the following steps sequentially: preprocessing and collecting information of vehicles and collected by intelligent bayonet systems and adopting an HBase distributed database to store vehicle flow data; utilizing the Hadoop distributed frame to conduct modeling and analysis on the vehicle flow data and the bayonet data, utilizing a Map-Reducer programming frame to achieve suspicious fake-licensed car recognition, conducting traveling track analysis on suspicious fake-licensed cars and building a fake-licensed car early warning information base. According to the method and the system, a distributed technology is adopted, the problem in the prior art that the fake-licensed cars cannot be recognized effectively due to large data processing quantity is solved, data above the TB level can be effectively processed, the fake-licensed cars can be found accurately, and the method and system provides a basis for the traffic management department to investigate the fake-licensed cars.

An integrated circuit is provided with multiple data processing components associated with respective sources which generate trace data streams. A reference timestamp generator is provided and the trace data streams are annotated such that they are output off-chip together with reference timestamp data. Outputting the reference timestamp data together with the trace data streams enables temporal correlation between points in different trace data streams by trace analysis tools.

A display format for a distributed system and method using a catalog definition language (CDL) based integrated trace analysis (iTAS) application for decoding telecommunication tracer information originating from any telecommunication network element and utilizing any industry standard or proprietary telecommunication protocol. User input to iTAS is provided using the appropriate form or forms on a browser-based graphical user interface (GUI). The display format of the browser-based graphical user interface (GUI) uses a common display page having three panes in which to display a tree view of trace events, a view of the decoded trace data, and a view of the original trace. For each original trace request partial results are displayed in the tree view and the decoded trace data, with regular updating until complete results are provided. The display provides for a plurality of concurrently pending original trace requests. The view within all three panes can be synchronized based on the selection of an event from the tree view pane. Further, any pane can be collapsed if required. Additional panes on the common display page are provided for controlling the display, searching and filtering the contents of the three panes, and displaying the progress of decoding.

Disclosed is a high-speed train driver alertness detecting method based on face image and eye movement analysis. The method includes steps of acquiring images of the head of a driver by a primary camera and a secondary camera simultaneously, extracting characteristics of the head of the driver step by step by the aid of wavelet multi-scale, recognizing the head of the driver via a neural network training method, and detecting the face of the driver via an AdaBoost arithmetic; respectively starting a Harr characteristic and a two-dimensional orthogonal Log-Gabor filtering phase characteristic to detect human eyes under different illuminations; building an adaptive non-linear level-log model of the driver; realizing eye movement tracking analysis for the driver via a strong tracking particle filter arithmetic; and finally realizing weight sum for an eye movement characteristic fatigue factor value and six face images including PERCLOS, pupilla, blinking, nodding, yawning and face inclination so as to obtain an alertness value of the driver. The calculated alertness value is high in accuracy and robustness.

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.

The invention discloses a public transport vehicle passenger flow statistical method and system. Concretely, two cameras are respectively installed at the front and rear doors of a bus. The release lines of the front and rear doors of the bus and a fitting function of the camera height and the head size are determined before processing images acquired by the cameras. After a door opening signal is received, preprocessing, head detection, head tracking and head movement track analysis are performed on the images acquired by the cameras in turn, and finally passenger behaviors are analyzed according to head movement tracks, the number of bidirectional passenger flow of the corresponding doors is acquired and the number of bidirectional passenger flow of the whole bus is acquired through statistics of the number of bidirectional passenger flow of the front and rear doors of the bus. After a door closing signal is received, processing of the images acquired by the cameras is stopped, and the problem of influence on the statistical result caused by abrupt change of illumination generated by movement of the bus can be reduced. The method has advantages of high statistical accuracy so that reliable supporting can be provided for intelligent scheduling of the bus.

The invention discloses a network quality monitoring method based on signalling and MR data. The method comprises the following steps: (1): analyzing the GGSNDATATEID, SGSNDATATEID, BeginTime and URI information through a S1-U interface, and extracting longitude and latitude information according to a longitude and latitude format; (2): obtaining XDR information through a S1-MME interface, associating the cell information through the ERAB_ULTEID, ERAB_ULTEID, BeginTime associated information; and (3): obtaining the RSRP data of an MR acquisition point through the cell information and start time with MRO data association. The method does not need to carry out a large number of on-the-spot tests, save resources, has strong stability, has the extensibility of long-term stable tracking analysis, can output the weak coverage area of the wireless network through association analysis and can optimize problems through the coverage accurate positioning network planing.

A trace analyzing apparatus, which includes a trace analysis table, an instruction reconstruction unit that reconstructs and sends an execution address and an instruction code of trace information, and an object code list storage unit, reads out an object code list and trace information, captures each piece of information in reverse order from the last stored address information stored in an address register, and then registers them in the trace analysis table.

The invention discloses a map data evaluation device, a map data evaluation system, a data acquisition system, an acquisition vehicle and an acquisition base station. The map data evaluation device comprises a data acquisition module, an analysis and judgment module, a quality evaluation module, and a registration accuracy calculation module. The data acquisition module is used for acquiring the data of the field operation of an automatic driving map in real time through a mobile network. The analysis and judgment module is connected with the data acquisition module and is used for analyzing and judging whether the acquired data of the field operation of the automatic driving map are lost or not, and outputting an analysis result. The quality evaluation module is used for carrying out panoramic image quality inspection and outputting an inspection result. The registration accuracy calculation module is used for carrying out track analysis on a panoramic camera and a laser point cloud based on the original data of laser scanning and the original data of the panoramic camera, detecting the registration accuracy based on the mutual information of laser scanning data and panoramic image data, and outputting a registration error. Therefore, the data quality of the acquired data of the field operation can be evaluated in time through the implementation of the invention. The acquisition quality and the production efficiency of map data are improved.

The invention relates to a device for tracking and early warning outburst danger of mine coal and gas in real time, consisting of a data acquisition system, tracking analytic center for data transmission and real-time data and integrated early warning and comprises the following components: a microseismic signal transmission rod, an ultralow frequency microseismic signal sensing element, a microseismic signal acquisition main computer and a three-stage integrated early-warning analysis and specialist diagnosing device. By an ultralow frequency mine-pressure dynamic sensor and a gas sensor, real-time tracking acquisition of an outburst risk signal of the coal and the gas can be realized for the first time; and the three-stage integrated early-warning analysis and specialist diagnosing device is established. The technology solves the problem that the outburst crustal stress of the coal and the gas cannot be monitored in real time and can improve the predicating accuracy of the outburst danger of the coal and the gas by over 90 percent.

The invention provides a video tracking analysis method and a system combined with geographic information. According to the invention, an object is confirmed and the characteristic information thereof is extracted through initialization, so the information of the object, such as, initial position, starting time, the next position and the required time spent in reaching the next position, is obtained; the video in the specific time section of the next position is subjected to matching; the position information is subjected to processing according to the matching result; and the path information of the object is stored and output. According to the invention, the camera relevance of a monitoring system is effectively utilized, the network space of the cameras and the time relevance is combined, and the object driving path can be automatically analyzed based on the geographic information obtained through the cameras.

The invention relates to a weak magnetism detecting instrument based on time-resolved remanence relaxation detection and application thereof. The detecting instrument consists of a detecting unit provided with a sensitive element with high sensitivity therein, a sample bracket, a pulse magnetic field generator, a signal data acquiring and converting system and a computer. The working principle of the detecting instrument is that the superparamagnetic nanomaterial is magnetized via pulse by means of a pulse magnetic field with a steep edge, then a magnetism sensitive element with a high sensitivity is utilized to carry out track analysis on the remanence relaxation generated by the superparamagnetic nanomaterial under the action of the pulse magnetic field, and then a quantitative detection of superparamagnetic nanomaterial is realized. By means of the instrument, biological analysis with high sensitivity can be realized by combining with nano-particles or magnetic beads. The instrument and method of the invention have fast detection speed, low cost, high sensitivity and good stability, and are suitable for fields of biological analysis, disease diagnosis, food security, environment monitoring and the like.

During a debug mode of operation of a data processor, it is determined at the data processor that a watchpoint event has occurred, and in response, an operating condition of a trace FIFO that stores trace information not yet communicated to a debugger is changed. For example, the occurrence of a FIFO flush watchpoint results in trace information being selectively flushed from the trace FIFO based on a state of the FIFO before the trace information has been communicated to a trace analyzer.

A system and method for automatically diagnosing protocol errors from packet traces is provided. The system and method performs an automatic trace analysis on a packet trace to generate an analysis that is then fed into a diagnosis / resolution module. The diagnosis / resolution compares the trace analysis with the database of known problems to identify the protocol error and a suggested solution. The suggested solution then may be implemented, either by a user or by the DR module, to correct the protocol error.

The utility model relates to a detection method of eye state based on cascade sort and Hough circle transform, belonging to the field of pattern recognition, which is characterized in the following steps: to acquire a face image; to carry out skin color segmentation in the YCbCr color space to acquire the position information of the skin color area using an ellipse skin model; to detect the rectangular eye area with the method of eye detecting window traversal with a cascade eye classifier; to merge a rectangle by rectangular merge method to get a merged eye rectangular linked list; to operate edge detection and binarization in turn on every rectangular eye area in the merged eye rectangular linked list with a Sobel operator to get an binary image; to detect the eye state of every binary image in turn with horizontal projection method; to further detect the eye state by Hough circle transform detection method if whether the present state is eye closure is not certain. The utility model increases the speed of eye detection, tracks and analyzes the eye state with the skin color segmentation, which is suitable for attention detection and fatigue detection.