984 results about "State recognition" patented technology

The system, method, and program of the invention captures actual physical gestures made by a participant during a chat room or instant messaging session or other real time communication session between participants over a network and automatically transmits a representation of the gestures to the other participants. Image processing software analyzes successive video images, received as input from a video camera, for an actual physical gesture made by a participant. When a physical gesture is analyzed as being made, the state of the gesture is also determined. The state of the gesture identifies whether it is a first occurrence of the gesture or a subsequent occurrence. An action, and a parameter for the action, is determined for the gesture and the particular state of the gesture. A command to the API of the communication software, such as chat room software, is automatically generated which transmits a representation of the gesture to the participants through the communication software.

The invention discloses a safe state recognition system for people on the basis of machine vision, aiming to solve the problem that the corresponding intelligent control decision for the vehicle driving behaviour can not be formulated according to the safe state of the people in the prior art. The method comprises the following steps: collecting a vehicle-mounted dynamic video image; detecting and recognizing a pedestrian in an interested area in front of a vehicle; tracking a moving pedestrian; detecting and calculating the distance of pedestrian in front of the vehicle; and obtaining vehicle real-time speed; and recognizing the safe state of the pedestrian. The process of recognizing the safe state of the pedestrian comprises the following steps: building a critical conflict area; judging the safe state when the pedestrian is out of the conflict area in the relative moving process; and judging the safe state when the pedestrian is in the conflict area in the relative moving process. Whether the pedestrian enters a dangerous area can be predicted by the relative speed and the relative position of a motor vehicle and the pedestrian, which are obtained by a vision sensor in the above steps. The safe state recognition system can assist drivers in adopting measures to avoid colliding pedestrians.

A system for allocating a wireless resource for a Space Division Multiple Access (SDMA) communication is provided. The system for allocating the wireless resource for the SDMA communication includes: a channel state recognition unit to recognize a channel state of wireless channels generated among adjacent nodes including a source node, a relay node, and a destination node; and a wireless resource allocation unit to control at least one of an amount of channel state information fed back from the destination node to the source node, and a relay level of a relay signal, the relay signal being generated by relaying a source signal transmitted from the source node, according to the channel state.

The invention discloses an eye positioning and eye state recognizing method, wherein first setting an self-adaptive threshold value to pretreat a face image, according to the face geometry character, designing an eye classifier, positioning eye initially, for some edge images, based on the symmetry face and eye, accurately positioning eye, thereby providing a method for positioning face symmetry axis based on lip auxiliary positioning, then dividing one eye from a positioned eye binary picture, according to the black pixel character of pupil, judging the eye state. The inventive method has real-time property, with the application for different backgrounds, lights, rotation and bias angles, and face details or the like to position eye and recognize eye state.

Operation state information for each cycle of manufacturing operations of each of injection molding machines 300 is acquired by a center management terminal device 400 via a network from a plurality of controlling terminal device 400 for controlling the injection molding machines 300. Cumulative utilization of replacement parts of each injection molding machine 300 put into practical operation is recognized by the operating condition recognizing section of the center management terminal device 400 based on the parts state information for the replacement parts of each injection molding machine 300 included in the operating state information. Based on the cumulative utilization, availability of the parts is recognized with reference to lifetime information concerning lifetime of the parts previously stored in the center storage section, and situation of the availability is displayed with a different display format on the center terminal displaying section 503.

The invention discloses a rolling bearing fault identification method under variable working conditions based on ATT-CNN, and relates to a rolling bearing fault identification technology. The problemthat the generalization ability of an existing rolling bearing fault recognition method under variable working conditions is limited to a certain extent for a complex classification problem is solved.The method comprises the following steps: firstly, mapping vibration data to a nonlinear space domain through a convolutional neural network (CNN), and adaptively extracting rolling bearing fault characteristics under variable working conditions by utilizing the characteristic that the CNN has invariance on micro displacement, scaling and other distortion forms of an input signal; Secondly, an attention mechanism (ATT) thought is put forward to be fused into a CNN structure, and the sensitivity of bearing vibration characteristics under variable working conditions is further improved; And meanwhile, more abundant and diverse training samples are obtained through a data enhancement method, so that the network can be learned more fully, and the robustness is improved. The proposed fault diagnosis model based on the attention mechanism CNN (ATT-CNN) can realize multi-state recognition and classification of the rolling bearing under variable working conditions, and compared with other methods, higher accuracy can be obtained.

The invention discloses a brain electric features based emotional state recognition method. The method comprises the following steps of: data acquisition stage: under the condition of international emotional picture induction, extracting 64 brain electric data which is tested under the induction of different-happiness-level pictures; data pretreatment stage: carrying out four stages of reference electric potential variation, down sampling, band-pass filtering, electro-oculogram removal on the collected 64 brain electric data; feature extraction stage: extracting time domain features after signals after pretreatment are filtered by a common space model algorithm; and feature recognition: recognizing the features by using a support vector machine classifier, and differentiating different emotional states. According to the method, an OVR (one versus rest) common space model algorithm is used for removing the interference of background signals, and is used for the signal intensification of multiple types of emotion induced brain electricity; after the background signals are removed, the differences among different types of emotional brain electricity are intensified, the recognition accurate ratio of subjects is relatively ideal when the recognition is carried out by the time domain variance features, and the emotions of different happiness can be differentiated accurately.

The invention discloses driver fatigue state recognition method and system based on information fusion, wherein the method comprises the steps of: acquiring eye state information of a driver, operating state information of a steering wheel and track driving state information of a vehicle; processing the eye state information of the driver, the operating state information of the steering wheel and the track driving state information of the vehicle to obtain fatigue expression information of the driver; and carrying out weighting fusion processing on the fatigue expression information to obtain a fatigue membership degree corresponding to a drive fatigue grade, and obtaining the fatigue degree of the driver according to the fatigue membership degree. The invention improves the reliability and the accuracy of monitoring the driver fatigue state, can reduce the quantity of traffic accidents caused by the fatigue driving of the driver, ensures the road traffic safety, and has strong practicability because the acquisition of multi-source information does not cause the interference on the driving of the driver.

The invention discloses an in-car detained passenger state identification and dangerous state control system. The in-car detained passenger state identification and dangerous state control system mainly comprises a monitoring unit for acquiring the internal state information of a car when the car is stopped. The monitoring unit comprises a passive pressure sensor module for monitoring pressure parameters of seats, and the module is used for judging the existence of detained personnel according to the pressure on the seats. As a feasible embodiment, the passive pressure sensor module can adopt a seat pressure parameter sensor in the prior art for detecting whether a passenger fastens a safety belt or not.

The invention relates to an expressway charge data track matching based traffic state recognition method, belonging to the field of intelligent transportation. Real road network charge data provided by an expressway management system is fully utilized to fully excavate the connotation of the charge data, then the charge data is processed, matched, analyzed and calculated to obtain the inter-site travel time and traffic flow of the whole road network, then a fuzzy clustering method is utilized to recognize the traffic state between any sites on the road network, and the method comprises the following four concrete steps: handling data exception; calculating the average travel time; calculating link traffic flow; and recognizing the traffic state based on fuzzy clustering. By utilizing the method, accurate traffic condition information can be provided for a manager, thus the manager can timely and accurately know the traffic state, and a reliable data basis is provided for developing anexpressway information service.

The invention discloses a human motion state recognition method and device. The method comprises the steps that a three-axis acceleration sensor and a human body sign sensor are arranged in a wearable device; it is determined that a human body is in the walking state according to acceleration signals collected by the three-axis acceleration sensor, the number of walking steps of the human body is calculated, and the walking stride frequency is calculated according to the number of walking steps; the corresponding sign frequency in the walking process is calculated according to sign signals collected by the human body sign sensor; the calculated walking stride frequency and the sign frequency are compared with a stride frequency threshold value and a sign frequency threshold value, and when the walking stride frequency is larger than the stride frequency threshold value and the sign frequency is larger than the sign frequency threshold value, it is determined that the human body motion state is the running state, and the calculated walking step number is recorded as running step number; or, it is determined that the human body motion state is the walking state, and the calculated walking step number is recorded as the walking step number. According to the technical scheme, the human motion state recognition method and device can effectively distinguish the walking state and the running state of the walking state.

The present invention discloses an improved full-convolutional neural network-based power transmission line insulator state recognition method. The method includes the following steps that: S1, the picture of a power transmission line insulator is collected through an unmanned aerial vehicle; S2, classification regression and position regression are performed on the image through a target detection network Faster R-CNN so as to intercept a separate insulator picture; S3, semantic segmentation is performed on the insulator picture through using a full-convolutional neural network; S4, fine segmentation is performed through a full-connection condition random field; S5, noise points in the image are filtered by using a morphological operation method; and S6, the insulator is classified through a deep learning classification network, and the status of the insulator is determined. According to the method of the invention, training and parameter adjustment and optimization are performed on labeled insulator pictures; the status of the power transmission line insulator can be effectively identified; the subjective influence of manual setting of thresholds and the randomness of manual extraction of features in traditional insulator status recognition can be avoided; the efficiency of line inspection can be significantly improved; and the difficulty of the line inspection can be decreased.

The invention discloses a method for identifying the traffic status of an express way based on information fusion, belonging to the technical field of traffic information fusion. The method comprises the steps: selecting traffic parameters, and establishing an evaluation index system of status identification; according to decision tree algorithm, establishing a binary tree structure of the traffic status identification; determining the fusion layer K of the binary tree structure, wherein K is more than or equal to 2 and i is equal to 1; according to sample format requirements of an ith layer, preprocessing data of the ith layer, and determining an input sample of the ith layer; utilizing a machine learning method of a support vector machine to train the input sample of the ith layer, thus obtaining the support vector machine; carrying out data fusion on the support vector machine to obtain a fusion result, and judging the support vector machine in next level fusion according to the fusion result; and if i is equal to i plus 1, judging whether that i is more than or equal to K is set, if so, returning the step 4, and executing the data fusion at next layer, and if not, ending the process. The method inherits the advantages of the information fusion method of the traditional support vector machine, and solves the problem of low accuracy of traffic status identification of the express way.

The invention discloses a network security situation awareness model and method based on an attack graph. The model comprises a data preprocessing module, an attack feature library construction module, an attack state identification module, a security situation evaluation module and a security situation prediction module. The method comprises: firstly, collecting data sets of different sources, and obtaining asset vulnerability threat data and asset attack threat data after preprocessing; further analyzing and training by utilizing the asset attack threat data and the principal component dataof the attack information, and establishing an attack feature library; matching the attack portrait, and determining the attack state of the current equipment; then, calculating a security situation value of the whole network by utilizing the asset attack threat data; and finally, predicting the next attack state through the attack and defense game matrix of the attack state diagram so as to predict the network security situation. A good situation awareness effect and a network security situation evaluation and prediction function are realized, and the model and the method have relatively goodpracticability, high efficiency and expansibility.

The invention provides a subway driver vehicular driving behavior analysis method, a vehicular terminal and a system. The method includes the steps: building a vehicular driving behavior database of asubway driver; acquiring a driver driving action recognition model and a driver face state recognition model through training by a deep learning method based on the vehicular driving behavior database; acquiring a real-time working video of the subway driver and extracting continuous multi-frame images according to a preset frame rate; acquiring the driving action track of the driver in the continuous multi-frame images, recognizing the driving action track by the driver driving action recognition model, and recognizing driver face states in the continuous multi-frame images by the driver face state recognition model. Driving behaviors and driving states of the driver can be monitored in real time and evaluated intelligently, possible manual operation errors can be early discovered, and driving safety is ensured.

The invention discloses a traffic safety sensing network based on mobile information for road intelligent traffic management. The traffic safety sensing network takes a vehicle as a mobile intelligent sensing node and forms into a sensing network with a mobile communication network and a traffic monitoring center. A vehicle-mounted positioning system and a vehicle-mounted sensor immediately acquire the position and the speed of the vehicle as well as the image information in and out of the vehicle, thereby providing real-time road traffic condition information to a traffic monitoring center; and a monitoring vehicle and the traffic monitoring center can perform various information interaction through a mobile communication network. With a vision sensor and a vehicle driving status identifying system, the traffic safety sensing network has the functions for acquiring and processing the image, can realize the functions for monitoring the illegal driving and reappearing the traffic scene, assisting the safe driving of the vehicle, provides a new traffic and vehicle supervising route for the traffic management department, can improve the traffic capability of the road, can improve the driving safety of drivers, and effectively avoids and reduces the personal injury and the economic loss caused by traffic accident.

An article transporting robot or an article transporting system includes a state recognizing means for recognizing the state of the article, a transportation method specifying means for specifying the transportation method according to the state recognized by the state recognizing means, and a transporting device for transporting the article according to the transportation method specified by the transportation method specifying means.