65 results about "Object dynamics" patented technology

An image pickup device includes an image pickup section that picks up a long-time exposure image and short-time exposure image; a combining section that combines the long-time exposure image and short-time exposure image with each other, to generate a combined image, the exposure images being combined on the basis of a ratio between the exposure time of the long-time exposure image and the exposure time of the short-time exposure image; a dynamic range calculating section that calculates an object dynamic range from the long-time exposure image, the exposure time of the long-time exposure image, the short-time exposure image, and the exposure time of the short-time exposure image; and a compressing section that, using base compression curve data, calculates a compression curve suitable for the object dynamic range, and generates a compressed image in accordance with the calculated compression curve.

The invention discloses a target object dynamic tracking and measurement positioning method. According to the method, two cameras are used for collecting images of a monitoring region; the backgrounds of the monitoring region are dynamically updated; a target object is extracted; a three-dimensional point cloud of a viewing angle region is generated by using a binocular identification positioning principle; the target object is dynamically tracked and positioned through combining the target object extraction and the binocular identification positioning principle. According to the method of the invention, vision distance measurement and target tracking are combined in the video monitoring field; the pixel coordinate of the image in which the target is located is determined; the target object is locked through combining the three-dimensional point cloud generated by the vision distance measurement; the three-dimensional coordinate of the target object is determined. When the target object enters a warning region, the system warns; therefore real time early warning is realized; the captured position information of the target object provides scientific basis for actual operation of a backstage worker.

Presented are automated driving systems for intelligent vehicle control, methods for making/using such systems, and motor vehicles equipped with such automated driving systems. A method for executing an automated driving operation includes: determining path plan data for a subject motor vehicle, including current vehicle location and predicted route data; receiving, from a network of sensing devices, sensor data indicative of current object position and object dynamics of a target object; applying sensor fusion techniques to the received sensor data to determine a threat confidence value that is predictive of target object intrusion with respect to the vehicle's location and predicted route; determining if this threat confidence value is greater than a calibrated threshold value; and, responsive to the threat confidence value being greater than the calibrated threshold value, transmitting one or more command signals to one or more vehicle systems (e.g., powertrain, steering and/or brake system) to take preventive action.

The invention relates to a D-axis and A-axis current vector composite controller of a permanent-magnet synchronous motor. The D-axis and A-axis current vector composite controller is characterized by comprising a position sensor, a speed measurement feedback link, a counter potential feed-forward compensator, a rotational speed closed-loop controller, an A-axis current composite controller, a D-axis current composite controller and a vector converter. By the D-axis and A-axis current vector composite controller, decoupling composite control is separately carried out on i<d> and i<q> under a dq coordinate, the speed regulation range is wide, phase shift of a phase current closed-loop control structure caused by limited bandwidth of the controller is prevented, and the D-axis and A-axis current vector composite controller has favorable performance in all ranges of speed regulation; through the adoption of a composite controls structure with combination of feed-forward and feedback, the dynamic characteristic is improved, the feedback control gain is reduced, and the gain margin of the system is improved; feed-forward is designed on the basis of the dynamic characteristic of an object, and D-axis and A-axis current vector composite controller is clear in physical concept, simple in structure and stable in working, and is easy to be implemented; and meanwhile, feedback control is introduced, the control precision is improved, and an error caused by model inaccuracy and disturbance is overcome.

The present invention provides a high-speed train real-time monitoring oriented mass data management method. According to the method, a two-layer storage architecture is formed by a distributed file system and a relational database, and a mileage triggered oriented window data management mechanism is established on an upper layer based on the relational database to realize the organization of monitored data; and by utilizing the distributed file system at a lower layer, balanced storage management of mass data is implemented. Ordered organization of the data can be realized in combination with a storage model of object dynamic coupling on the basis; and meanwhile, by using a way of global-local property delivery management and establishing mileage accumulated triggering for trains, demands of train monitoring and analyzing are met. Aiming at high-speed train real-time monitoring, the high-speed train real-time monitoring oriented mass data management method provides core technologies of massive and cross-discipline data management under the large data background and has active application value in the fields of transportation, logistics, smart city and the like.

A method and apparatus for tracking objects across images. The method includes retrieving object location in a current frame, determining the appearance and motion signatures of the object in the current frame, predicting the new location of the object based on object dynamics, searching for a location with similar appearance and motion signatures in a next frame, and utilizing the location with similar appearance and motion signatures to determine the final location of the object in the next frame.

Embodiments of the invention disclose a dynamic model three-dimensional rebuilding method, apparatus and device, and a storage medium. The dynamic model three-dimensional rebuilding method comprises the steps of acquiring a current frame depth image of a target object and a current frame color image corresponding to the current frame depth image; obtaining a second target object reconstruction model by utilizing the current frame depth image and a first target object reconstruction model; and according to the current frame color image and a key frame in a front color image, determining color information of each vertex in the second target object reconstruction model, wherein the first target object reconstruction model is a target object reconstruction model corresponding to a previous frame depth image, the second target object reconstruction model is a target object reconstruction model corresponding to the current frame depth image, and the front color image is each frame color image obtained before the current frame color image. According to the rebuilding method, apparatus and device, good interactive target object dynamic model three-dimensional rebuilding experience is provided for a user.

The invention discloses a moving object detection and tracking method based on an improved ViBe algorithm, and the method specifically comprises the following steps: S1, employing a strategy for judging the stability of a video before the initialization of a ViBe background model, and employing a plurality of stable input frames, which do not need to be continuous, for constructing the background model after the stabilizing of the video; S2, carrying out the first background model correction after ViBe extracts a foreground image; S3, carrying out the second background model correction after the detection and tracking of a moving object; S4, carrying out the matching of a moving object frame set in a current frame with a moving object dynamic rectangular frame set constructed by a moving object frame set in a former time period through employing geometric comparison during the positioning and tracking of the moving object. The method improves the background stability, reduces the background noise and misjudgment probability, solves a shadow leftover problem, and reduces the calculation complexity of positioning and tracking.

The invention relates to an analog system and an analog method of dynamic electromagnetic scattering characteristics in space object convergence, and is used for testing experiment of dynamic electromagnetic scattering characteristics in space object convergence under ground conditions. The system includes a radio-frequency system, an instrument automatic control system, a scanning support and a control system that are in circuit connection as well as an object hanging system. The analog method is that an interval is set for each stepping to test the amplitude and phase of the back wave of the object during the convergence, so as to extract Doppler characteristic signals. The scanning support and the object hanging system can be combined in a moving way in the laboratory to analog the convergence movement of the space object, so as to perform the analog testing research of the object dynamic electromagnetic scattering characteristics during the space convergence, as a result, the scattering characteristic data of the required object can be obtained, and the urgent demand of the autonomous convergence technology research of the object can be satisfied.

The invention is applicable to the field of computers, and provides a dynamic object recognition method, a computer device and a readable storage medium. The method comprises the steps of obtaining image information of a to-be-identified area, wherein the image information comprises environment information and target object information; extracting target object feature information according to theimage information; determining a target object area according to the target object feature information; based on the target object feature information, constructing a target object dynamic analysis model; judging whether the target object area conforms to the prediction result of the target object dynamic analysis model or not; and if the judgment result is yes, determining the target object areaas a target object, and outputting a recognition result. By implementing the method and the device, the influence of dynamic blur generated in the moving process of the object on the recognition effect can be overcome under the condition that the hardware limitation is not exceeded, and the problem that the recognition effect of the object is poor due to the fact that the change of the characteristic value is fast and uncertainty exists in the moving process of the object is solved, so that the recognition accuracy of the dynamic object is improved.

The invention discloses a space teleoperation mechanical arm on-orbit training system and method, and belongs to the technical field of space stations. Firstly, a trainer selects training scenes through an interactive interface, and physical characteristic parameters of a target object can be customized in each scene. Scene initial conditions are then set. After simulation is started, target object dynamics model related to the set parameters can be displayed in a virtual image mode through the augmented reality technology and fused with a real environment image, and the fused virtual-real combined image is input toVR glasses worn byan operator. The virtual target image is driven by data of the target object dynamics model to simulate real target dynamics characteristics. When an operatoruses the teleoperation device to control the mechanical arm to execute corresponding actions, the contact and collision process of the tail end of the mechanical arm and a target object and the stresscondition after collision can be simulated, so that the operator can truly feel the influence of different task loads on the mechanical arm and the influence on the attitude of the space station.

The invention discloses an object dynamic angle measure method and its device, involving in measurement technology; the resolved measurement technology is the measure of the object dynamic angle; the measurement as the following step: 1) dynamic measure the acceleration: using the acceleration indicator to dynamic measure the acceleration weight aX, aY of X-axis, Y-axis; 2) wireless transmission test data; using the RF transmitter and RF receiver module to test data - the wireless transmission of the acceleration weight aX, aY; 3) computing the dynamic angle of object: the dynamic deviation angle of the object round X-axis: theta x = 5.8480ay-0.4006r; dynamic angle of the object around Y-axis: theta y = 5.8480ax-0.4006r. The invention has low cost, long transmission distance, and can solve the test problem of the object dynamic angel by measure of the acceleration and can real-time wireless measure the dynamic angel of the scene object.

The invention discloses a target tracking algorithm under dynamic and static backgrounds, and the algorithm comprises the steps: firstly, importing to-be-detected video or picture stream data, and cutting a target region based on a first frame image; secondly ,performing target object correction in the first step, wherein generally, standard information exists in the first image so that correctionis mainly carried out on target objects in a second frame and all frames after the second frame, and the target objects are made to be located in the center of the frame as much as possible; second correction is mainly used for solving the problem of deviation correction of the target object under the condition that the first correction is inaccurate, and the two corrections ensure that accuratetarget object dynamic tracking can be realized no matter how the target object moves or how the camera moves; cutting out a new area in the frame (namely the frame analyzed at the present moment) by utilizing the corrected position information to serve as a basis for tracking the next frame; reading the next frame, judging the position of the target object in the current frame based on the corrected area of the previous frame, and selecting the target object from the original image; and continuously correcting in sequence until detection is finished.