610results about How to "Good tracking effect" patented technology

A disk drive that includes a base, a magnetic disk, a rotary actuator that carries a head for reading and writing data from the disk in a track-following mode under the control of a servo control system, and at least two sensors--one fixed sensor rigidly coupled to the overall disk drive and one mobile sensor mounted to the rotating actuator--for differentially detecting accelerations of the rotary actuator relative to the overall disk drive and its disk. The disk drive detects and actively compensates for accelerations imparted to a balanced actuator that has an effective imbalance. The fixed sensor is preferably mounted to a PCBA that is secured to the base. The mobile sensor is preferably mounted to an actuator arm of the rotary actuator, as far outboard as possible, and so as to align with the fixed sensor as the rotary actuator swings through its range of travel. The preferred sensors are linear accelerometers.

The invention discloses an intelligent control method of a driverless vehicle tracking a desired trajectory. The method is characterized by comprising the following steps of: establishing a body coordinate system, and determining the position information of the vehicle; calculating a membership degree function of a road curvature characteristic according to a radian value, and defining a fuzzy rule to calculate a decision output speed; according to the distance the vehicle runs for 1.5-2.5 seconds, searching for the trajectory points larger than the distance and closest to the vehicle in the coordinate sequence of the desired trajectory; calculating the moving curvature of the vehicle according to an adaptive proportion-differential-integral control algorithm formula; and finally judging whether the target point of the current control cycle is the last point selected from the road point sequence; if so, outputting a signal to a brake servo control system to start the brake to slow down the vehicle; otherwise, outputting a voltage signal by a controller local area network module to keep and control the accelerator opening so that the vehicle continues proceeding. Through adoption of the intelligent control method, the driverless vehicle can realize a function of tracking the desired trajectory, and has certain adaptability to the change of the road curvature characteristic.

A novel and useful channel tracking mechanism operative to generate channel estimate updates on blocks of samples during reception of a message. The tracking mechanism is based on the weighted recursive least squares algorithm and implements the estimation process by recursively updating channel model parameters upon the arrival of new sample data. The mechanism is operative to update channel estimate information once per sample block. An interblock exponential weighting factor is also applied. The block length is chosen short enough to enable good tracking performance while being sufficiently long enough to minimize the overhead of generating preliminary decisions and of updating precalculated tables in the equalizer. The method of the invention can be performed in either hardware or software. A computer comprising a processor, memory, etc. is operative to execute software adapted to perform the channel tracking method of the present invention.

Disclosed herein are a method for tracking object in video in real time in consideration of both color and shape and an apparatus for the same. The apparatus may generate at least one of a correlation filter model and a color probability density model based on an input image, determine an initial position and an initial size of a target to be tracked based on a correlation filter response value calculated by applying the correlation filter model to the input image, calculate a joint probability based on the correlation filter response value and a color object probability that is calculated based on the color probability density model, and update an object model corresponding to the target to be tracked based on a final position and a final size of the target to be tracked, which are determined by applying the joint probability to the initial position and the initial size.

The invention relates to a catheter. A catheter wall thereof sequentially comprises a smooth layer, a strengthened layer and a jacket layer from inside to outside, wherein the smooth layer and the jacket layer are both formed by compounding polymer materials, and the strengthened layer is a support layer and is respectively connected with the smooth layer and the jacket layer, therefore, every two layers of the catheter are connected. The catheter also sequentially comprises a proximal end part and an extension part along the direction from the near to the distance. In addition, the strengthened layer is in a braided structure at the proximal end part and is in a spiral structure at the extension part. The invention has the advantages that the structure can enhance the flexibility, the torsional resistance, the tracing property, the supporting property and the anti-fold property of the catheter when reducing the size of the catheter, and therefore, the catheter is suitable for penetrating through a distal vessel in a cranium.

An automatic moving object tracking device and a method thereof are capable of tracking a moving object through a signal process of an input image signal of each frame. The moving object tracking device converts a pre-processed input image signal into a binary disturbance image signal, and calculates a motion value of each pixel through an initial tracking window. After locating the tracking window at the pixel where the motion value is a maximum value, a size of the tracking window is adjusted so that the tracking window can include the moving object therein. Next, based on acquired information about the moving object and the tracking window and previously acquired information about previously frames, a pixel in a following frame is estimated to be a next location of the moving object. The tracking window is positioned at the estimated pixel. If the tracking result is satisfied, the tracking of the moving object continues.

The invention discloses antenna beam tracking device and method of a moving communication satellite communication system. The antenna beam tracking device comprises a geographical position detection device, a carrier gesture detection unit, a signal intensity detection unit, a signal conditioning circuit and a master control computer, wherein the master control computer controls a servo driver; and the servo driver controls an azimuth and pitching motor. The antenna beam tracking method comprises the following steps of: 1, initially capturing a target satellite; 2, tracking: setting initial parameters, storing and updating the initial parameters in real time, generating simultaneous disturbance random vectors, driving disturbance, measuring the intensity of received signals, estimating gradient, determining tracking error signals, regulating antenna beam pointing directions, and judging the received signals; and 3, recapturing. The invention has the advantages of simple design, low cost, system implementation without changing the hardware structure of an original tracking system, easy operation, high tracking accuracy and fast tracking speed and overcomes the defects of inconvenient operation, complex tracking step, lower tracking accuracy and tracking speed, and the like of the traditional method.

The invention discloses a quad-rotor UAV fault tolerance control method based on an adaptive fault estimation observer, and belongs to the field of aviation aircraft control. The method comprises thata fault model of a quad-rotor attitude system is established according to a dynamic model of a quad-rotor UAV by considering a performer fault of a UAV system; a performer of the UAV includes four rotor motors in practicality, faults correspond to the four rotor motors, the fault model is processed, the faults are divided into two groups decoupled mutually, and a final attitude fault model is obtained; according to the provided fault model, the adaptive fault estimation observer is designed, corresponding adaptive laws are provided, the performance fault is estimated, and an H(infinite) method and an interval matrix method are used on external disturbance and parameter nondeterminacy respectively in the design process; and an attitude system error fault model is obtained on the basis of the fault model, a dynamic output feedback fault tolerance controller is designed on the basis of a fault estimated value, and fault tolerance control of the quad-rotor UAV is realized. Influence of the performer fault on performance of the quad-rotor UAV can overcome, and the safety and reliability of the UAV in the flight process are ensured fully.

The embodiment of the invention provides a track-shooting method, a track-shooting device and an unmanned aerial vehicle, and aiming at solving the technical problem of different tracking effects caused by quite different image processing capabilities of a mobile terminal since images are processed by the mobile terminal and transmitted to the unmanned aerial vehicle for tracking when the unmanned aerial vehicle is used for performing track shooting in the prior art. According to the track-shooting method and device, an alternative target is generated by the unmanned aerial vehicle according to collected image information and a preset target characteristic value, and a track target is generated according to the alternative target for track-shooting, so that the technical effect that the track target for track-shooting is benefited by consistent processing effect since the unmanned aerial vehicle is used for processing images can be achieved.

A stent delivery system comprises a delivery catheter with a balloon and a stent. The stent delivery system is characterized in that when a force to move the stent in the axial direction of the catheter is applied to the stent, a holding mechanism is formed in a part of the balloon to prevent the stent from falling down. According to this invention, the stent delivery system that is capable of preventing the stent from falling down and has excellent track ability can be provided without requiring complicated manufacturing processes.

The invention relates to a method and a device for detecting and tracking a target image, belonging to the technical field of video monitoring. The method comprises the following steps of: detecting a target in a video image frame, and establishing an initial histogram model of the target according to an area in which the detected target is located; carrying out area detection on a subsequent video image frame, and establishing ta tracking histogram model of the target according to the detected area; according to the similarity of the initial histogram model of the target and the tracking histogram model of the target, determining the dimension of the target image at the current time and the central position of the located area, and judging whether the initial histogram model of the target is updated or not; according to the central position of the video image of the current time and the central position of the located area of the target of the current time, adjusting the rotating direction and the speed of a camera head, and adjusting the focus of the camera head according to the dimension of the target image. The invention can be used for detecting and tracking the target in a big scene so as to improve the effect of detecting and tracking the target in the big scene.

The invention discloses a multi-scale target tracking method based on background suppression and foreground anti-jamming, which relates to the technical field of target tracking. The method includes the following steps: constructing and initializing a color probability model and a DCF tracking model; using an adaptive Gaussian window function to suppress the background in the previous frame of image, calculating the filter response map of a target position based on FHOG features in the previous frame of image, calculating the color probability distribution of the previous frame of image, obtaining the color response map of the target position, linearly fitting the filter response map and the color response map, and predicting a target position of next frame of image; updating the scale information of the target in the next frame of image according to the predicted target position of the next frame of image and based on a scale pyramid model; and carrying out adaptive dense sampling according to the target position and scale information of the next frame of image, calculating the FHOG features and color histogram of the next frame of image, and updating the DCF tracking model and the color probability model.

The invention relates to a model-free adaptive optimized control method for a PVC polymerization process, and relates to an optimized control method for the polymerization process. The PVC polymerization process is a complex industrial process characterized by high inertia, large lagging and non-linearity. A model-free adaptive controller algorithm is designed aimed at a common discrete time non-linear system; particle swarm optimization is used to optimize and set key parameters of the controller; a model-free adaptive optimal controller is used to control a polymerization temperature system obtained by least squares identification; and a simulated experiment result shows that the model-free adaptive controller algorithm based on particle swarm optimization can obtain better control performance indexes.

The invention provides a method and a device for tracking and locating a target for an aircraft. The method includes the steps: calibrating a first airborne camera and a second airborne camera so as to obtain calibration parameters; appointing characteristic information of the target needing to be tracked and located; correcting a first camera image and a second camera image obtained by the first camera and the second camera according to the calibration parameters; generating an anaglyph with a first camera corrected image as a standard according to the first camera corrected image and a second camera corrected image; tracking the target to obtain a target area where the target is located by referring to the characteristic information and by using the first camera corrected image and the anaglyph; and extracting characteristic points of the target area in the first camera corrected image, matching the characteristic points with the second camera corrected image, and calculating position information of the target according to the successfully matched characteristic points. By means of the method, the target can be tracked better, and the position information of the target can be obtained.

The invention discloses an indoor positioning method based on improved square root unscented Kalman filtering. The method comprises the following steps of firstly, establishing a UWB positioning modeland a pedestrian dead reckoning PDR model in a fusion indoor positioning method; then, according to a residual identification method criterion, determining whether an NLOS criterion exists in a positioning result of the UWB positioning model; if the NLOS exists, using an improved square root unscented Kalman filtering algorithm to fuse a coordinate of inertial navigation dead reckoning with a positioning coordinate of UWB, and correcting a UWB solving coordinate data; and if the NLOS does not exist, using the UWB to analyze a current coordinate and completing real-time positioning. In the invention, the pedestrian dead reckoning PDR is used to compensate a UWB signal loss or non-line of sight condition, which improves the positioning accuracy of the system and the advantages of high precision and high robustness are possessed.

The invention discloses a low-altitude defense system of an unmanned aerial vehicle. The low-altitude defense system is characterized by comprising a detection and recognition system, a photoelectrictracking system and an interference inversion system, wherein the detection and recognition system is used for performing scanning, detection and early warning of an invading unmanned aerial vehicle;the photoelectric tracking system is used for identifying, tracking and locating the invading unmanned aerial vehicle, and determining the coordinates of the intruding unmanned aerial vehicle; and theinterference inversion system is used for interfering or controlling the unmanned aerial vehicle. In the low-altitude defense system of the unmanned aerial vehicle, multi-sensor fusion front-end signal acquiring equipment is adopted, so that various parameters can be obtained, and the intruding unmanned aerial vehicle can be found and tracked in time. Meanwhile, automatic defense of the unmannedaerial vehicle is realized through linkage among systems.

A target detecting and tracking system using a background differencing method based on FPGA comprises a FPGA device, a SD card, an LED indicator light, a DDR2SDRAM, two seven-segment digital tubes, an LTM display screen and a minimum video detecting and tracking system, wherein the minimum video detecting and tracking system is embedded in the FPGA and is integrated in a SOPCbuilder environment with an AVLON bus as a standard. The target detecting and tracking system using the background differencing method based on FPGA is mainly used for detecting and tracking moving objects in static scenes. A target detecting and tracking method using the background differencing method based on FPGA comprises the steps of a. reading AVI format video files with the SD card, b. converting the AVI format video files into multiframe images, c. detecting and tracking the videos based on the images, d. obtaining the moving objects which are to be tracked, and e. displaying tracking results on the LTM display screen. Due to the fact that an FPGA platform is adopted by the system, the system is high in parallelism performance, and computing speed is improved. The target detecting and tracking method is good in tracking effect and adaptability, particle filter algorithm which is suitable for non-linear non-Gaussian dynamic models, and the target detecting and tracking system is similar with real scenes and is good in adaptability and high in tracking accuracy.

The invention relates to a fast object recognition algorithm comprising the following steps of: firstly, carrying out median filtering on approximately one second sequence frame in time domain so as to be taken as a static background; secondly, determining a moving object by utilizing the fusion algorithm of background subtraction and interframe difference; thirdly, carrying out binaryzation on the obtained result by utilizing maximum variance threshold segmentation, and simultaneously analyzing the effectiveness of the segmentation; and finally, merging the results of the effective segmentation, and tracking by utilizing Kalman filtering. The intelligent video object-tracking method has good tracking effect and high robustness, dispenses with manual intervention and effectively avoids the phenomena of tracking and alarming by mistake.

A thermometer code to sign and magnitude converter that is particularly useful in a flash ADC is provided. This comprises two conversion units. The first is a thermometer code to Gray code converter and the second a Gray code to sign and magnitude converter. Preferably, the Gray code is of a kind that has a sign bit and has the other bits symmetrically disposed about zero. This form is easily converted to a sign and magnitude code, which is advantageous as it reduces the latency of the converter, which is particularly useful at high data rates.

The invention discloses a moving object relay tracing algorithm of multiple PTZ (pan / tilt / zoom) cameras. The moving object relay tracing algorithm is characterized in that the moving object relay tracing algorithm is carried out according to the following steps: 1. estimating inner parameter matrixes of the PTZ cameras by adopting a camera self-calibration method; 2. setting a view cutting line between adjacent PTZ cameras; 3. using Logistics regression model as a classification function, and combining with a mean value drifting algorithm and realizing the target tracking; 4. continuously adjusting angles of the PTZ cameras in the course of tracking, so that the target is always located in the center zone of the PTZ camera view; 5. when the target exceeds the view cutting line of the PTZ camera at present and enters the monitoring view of the adjacent PTZ camera, calculating the coordinate of the target in the adjacent PTZ camera view, and transferring the adjacent PTZ cameras to track the target, and rotating the original PTZ camera to return the preset position. The moving object relay tracing algorithm can accurately control the camera rotation, and perform stable tracking for a long time on the target; and thereby, the complete historical movement information of the target can be obtained.

The invention belongs to the technical field of welding automatic control, and particularly relates to a magnetic control rotating arc sensing real-time weld joint tracking system and a magnetic control rotating arc sensing real-time weld joint tracking method. The technical point is that a magnetic control rotating arc sensor is applied to automatically tracking a weld joint; a rotating magnetic field is exerted to the welding arc, so that the weld joint can be scanned through the welding arc at a certain frequency, and then the characteristic parameter for showing the position of a weld gun relative to the position of the weld joint can be acquired; a hall sensor is used for acquiring a welding current signal, and the welding current signal is fed into a control system to be subjected to digital filter and corresponding program operation; and a tracking performing mechanism is controlled to properly adjust the weld gun, therefore, the weld gun can be aligned to the center of the weld joint so as to track the weld joint. With the adoption of the system and the method, the requirement on automatic tracking of the weld joint can be met; the weld gun is directly arranged on the magnetic control rotating arc sensor, and the problem due to front installing and rear installing can be avoided; and the system and the method have the characteristics of being good in real-time capability, low in cost, high in stability and high in precision.

The invention discloses an adaptive ORB object tracking method. The adaptive ORB object tracking method adds FAST characteristic direction information in order to solve the problem that the FAST characteristic has no direction; a BRIEF characteristic descriptor based on pixel point binary digit comparison is adopted in a characteristic point description portion; the defects that the BRIEF descriptor is sensitive to the image noise and has no rotation invariance are improved; and compared with an SIFT algorithm, the ORB algorithm has the rotation invariance and noise resistance, and the operation speed of the ORB algorithm is higher than that of the SIFT algorithm by two orders of magnitude. The adaptive ORB object tracking method fully utilizes the characteristic of the ORB algorithm, performs further improvement on the PRB algorithm, brings forward the ORB algorithm on the basis of that the improvement, further improves the operation speed and the tracking accuracy, and better meets the demand for the real-time tracking.

The invention provides a Mean shift moving object tracking method based on compressed domain analysis; in the method, the compressed domain analysis and a Mean shift tracking algorithm are combined, probability statistics analysis is carried out to motion vector generated in the video coding process, so as to obtain estimated value of object moving direction and moving speed, so as to correct the central position of a Mean shift moving candidate region and lead the candidate central position to close to the central position of the practical object when the searching starts at each time. In the technical proposal, the tracking precision of the rapid moving object is improved, the searching iteration times of the algorithm are reduced, and the operation efficiency is improved. The proposal is particularly suitable for situation that the video coding and object tracking in the intelligent video monitoring equipment are carried out at the meantime.

The invention discloses a video object tracking method based on a feature optical flow and online ensemble learning. The technical problem that tracking results of a tracking method of a specified object in an existing digital video are poor is solved. According to the technical scheme, the method comprises steps of inputting a tracking portion into a video sequence, tracking characteristic points of every frame through an iterative pyramid optical flow method by using functions of OpenCV, and obtaining positions of characteristic points of the next frame; selecting a positive sample or a negative sample to be subjected to adaboost algorithm processing for a detection portion; and conducting machine learning for possible object positions obtained by the tracking portion and the detection portion. A tracking feature extraction mode and a detection feature extraction mode are separated, the filtering for possible object position limitation is conducted during detection, possible objects which are far away from objects are removed, after tracking results and detection results are obtained again, the fisher discrimination ratio of objects and the online model is calculated in a self-adapting mode, the corresponding weight is determined, a fixed value is not used for fusing two results, and then the tracking effect is good.

The invention belongs to the field of cell tracking, and discloses a method for synchronously tracking multiple cells in a high-adhesion cell environment. In a cell sequence image, how to divide and synchronously track the cells is an unsolved problem, and especially the problem of tracking and dividing the cells under the high-adhesion condition urgently needs to be solved. An improved dividing algorithm based on watersheds and multi-feature matching is firstly provided to achieve cell dividing, then a motion model suitable for Kalman filtering is built, the multi-feature matching is added to achieve cell predication and tracking. Through experimental verification, the method is effective, the average effective rate of dividing sequence frame cells is 94.4%, and the tracking effect is superior to that of the tracking method in the prior art.

The present invention relates to a device for obtaining a vital sign of a subject, comprising an interface (20) for receiving a set of image frames of a subject, a motion analysis unit (30) for analysing at least one measurement area within the image frames of said set of image frames and for characterizing motion of the subject within said set of image frames, a signal extraction unit (40) for extracting photoplethysmographic, PPG, signals from said set of image frames using said characterization of motion of the subject within said set of image frames, and a vital signs determination unit (50) for determining vital sign information from said extracted PPG signals. The motion analysis unit comprises a motion estimation unit (32), a spatial characteristic extraction unit (34), and a motion characterization unit (36).

The invention discloses an unmanned surface vessel linear tracking method based on a fuzzy PID. The method includes the following steps of dynamically obtaining a course angle of an unmanned surface vessel and real-time longitude and latitude coordinate values by means of a GPS device, calculating a distance deviation and an angle deviation by means of a vector cross product method, dynamically adjusting a parameter value of the PID by means of the fuzzy relationship between the distance deviation and the PID parameter and the angle deviation and the PID parameter, calculating control voltages U of a left electric propeller and a right electric propeller, and pushing the surface vessel to advance after control voltages are applied to a motor. As is shown by simulation and experiment results, the method has good tracking effects on the condition that a straight slope, a USV starting point and a starting angle are different, has good adaptability, can effectively avoid U-turn phenomena, and is superior to a PID controller in linear tacking performance.

The invention discloses a Mean shift-based video target tracking method, which extracts the SIFT characteristics of the tracking target and then matches the SIFT characteristics of the target by the Mean-Shift algorithm to realize the target tracking. The method makes full use of the characteristics of invariance against rotation, size scaling and brightness change and high resistance against noise interference and the like. The invention not only considers the real-time performance of the algorithm, but also can well solve the problems of size scaling, object obstacle, rotation, illumination change and the like. The technology has wide application prospect and development potential in the fields of safety monitoring, automobile auxiliary movement, human body movement analysis, robot vision and so on, and can improve the real-time performance and accuracy of the target tracking.

The invention discloses an electromechanical servo system friction compensation and variable structure control method based on a neural network. The electromechanical servo system friction compensation and variable structure control method based on the neural network includes steps: building an electromechanical servo system model and a Lugre friction model, and initializing system status and related control parameters; estimating friction force through the neural network, and compensating the friction force into a system. A linear extended state observer is designed and used to estimate non-measurable system status and uncertain items including parameter perturbation and neural network estimation errors. A sliding mode variable structure controller is designed according to the system status and the parameter perturbation which are estimated by the linear extended state observer, and therefore the electromechanical servo system friction compensation and variable structure control method based on the neural network guarantees that system trace errors can rapidly and stably converge to a null point, and achieves rapid and stable control for an electromechanical servo system.