207 results about "Video imaging" patented technology

The invention discloses a digital coding metamaterial forward-looking video imaging method and system based on sparse low-rank decomposition, and mainly solves the problems of motion blur and poor imaging stability in a non-sparse observation scene of a moving target in the prior art. According to the implementation scheme, echo data of N frames of observation scenes are collected; decomposing a scattering coefficient vector of an observation scene corresponding to each frame of echo into a low-rank vector of a background area corresponding to the observation scene and a sparse vector of a dynamic change area, and expressing a separation problem of the two change areas as a joint low-rank and sparse optimization problem; performing convex relaxation processing on the optimization problem, and converting the optimization problem subjected to the convex relaxation processing into an optimization problem in an unconstrained form to obtain a sparse low-rank decomposition-based metamaterial forward-looking video imaging model; and solving the constructed imaging model, and realizing multi-frame image reconstruction and video synthesis based on a solving result. According to the method, the imaging resolution and reconstruction stability of the non-sparse scene containing the moving target are improved, and the method can be used for intelligent security check and medical detection.

The invention discloses an unmanned aerial vehicle dynamic projection map construction method and system based on spatio-temporal data fusion, and belongs to the technical field of unmanned aerial vehicle video monitoring and geographic scene fusion, and the method comprises the steps: obtaining multi-modal flight data in real time based on an unmanned aerial vehicle, and the multi-modal flight data comprise video image data and spatio-temporal reference data; and performing data preprocessing on the multi-modal flight data to obtain route data. And constructing an unmanned aerial vehicle dynamic projection model, and performing space-time synchronous projection rendering on the route data to obtain an unmanned aerial vehicle dynamic projection map. And constructing a dynamic calibration model, and correcting the dynamic projection map of the unmanned aerial vehicle. According to the method, an integrated dynamic geographic information sensing system is constructed through deep cooperation of a spatio-temporal data fusion framework and an intelligent calculation engine, accurate mapping of the geographic space driven by spatio-temporal reference fusion is realized, millimeter-level space registration capability is constructed through multi-modal data intelligent solution and terrain adaptive rendering, and the real-time dynamic geographic information sensing system is constructed. And a technical breakthrough is formed in the dimensions of accurate positioning, data fusion, real-time response and the like.

1. The name of the design product: projector. 2. The use of the design product: projecting text, patterns and video images. 3. The design points of the design product: in shape. 4. The picture or photo that best shows the design points: perspective view 1.

The invention discloses a near-shore wave breaking type classification method based on video image deep learning. The method comprises the steps that video image data of a near-shore area are collected based on fixed or temporary video collection equipment, and the visual angle of the video image data covers the high position of a near-shore wave breaking zone; preprocessing the video image data, and marking overflow waves, curled waves and collapse waves according to the data; constructing a training set based on the marked data, and training a neural network model based on the training set; and based on the trained neural network model, carrying out feature extraction and time sequence modeling on the coastal wave image sequence, and predicting a wave breaking type corresponding to the coastal wave image sequence. According to the method, the time sequence video data is collected, and the deep learning model is constructed for training and reasoning, so that wave breaking type identification is automatically completed. The method is efficient and reliable, can adapt to various sea conditions, and has high practical value in practical application.

The present invention provides a method for extracting features of the nearshore wave breaking process based on time series video images; wherein, the method comprises: setting at least one pixel sampling area in a plane geographic coordinate system, collecting time series video images of ocean nearshore waves, quickly converting them into plane geographic coordinate images through a coordinate model, and then stacking cross-shore pixel values ​​of several pixel sampling areas within a set time to generate a cross-shore pixel value and time relationship sequence diagram, mining the time-varying signal of the wave propagating toward the shore, combining the geometric relationship between the camera angle of view and the plane projection of the wave breaking, and calculating key wave breaking features such as the wave breaking point position, wave breaking water depth, and wave breaking height; the method can continuously monitor the nearshore wave breaking features efficiently, automatically, and stably, effectively making up for the shortcomings of traditional monitoring and analysis methods, and providing strong technical support for the refined research and management of nearshore beach dynamic landforms.

The invention relates to the technical field of biomedical engineering, and discloses a tumor minimally invasive surgery risk assessment model construction method and system, and the method comprises the steps: recognizing a potential failure mode of a tumor minimally invasive surgery through employing an intra-operative video image and operation process data; calculating a risk priority index of the potential failure mode in the tumor minimally invasive surgery so as to determine a high-risk failure mode of the tumor minimally invasive surgery; setting a grading risk management layer of the tumor minimally invasive surgery by using the risk score and the high-risk failure mode of the patient in the tumor minimally invasive surgery; a failure correlation analysis network of the patient in the tumor minimally invasive surgery is constructed, and a risk prompt unit of the tumor minimally invasive surgery is generated; and constructing a risk assessment model of the tumor minimally invasive surgery in combination with a risk prompt unit, a hierarchical risk management layer and a failure association analysis network. According to the method, the high-risk failure mode can be accurately positioned, and the accuracy and comprehensiveness of model risk assessment are improved.

The invention discloses an ocean current monitoring method, device and equipment based on a video image and a storage medium, and relates to the technical field of ocean current monitoring, and the method comprises the steps: carrying out the preprocessing of a video image of a target sea area, and the preprocessing comprises the framing processing and optical flow calculation of the video image; extracting spatial features of water surface ripple shapes and floating object distribution from the preprocessed video images through a spatial flow network; capturing time sequence characteristics of tidal cycle and vortex evolution of the preprocessed video image through a time flow network; the spatial features and the time sequence features are fused as spatial-temporal features, and ocean current parameters are calculated based on motion vector integration; eliminating noise interference of ocean current parameters based on multi-scale data fusion so as to generate an ocean current field distribution model; and monitoring the ocean current of the target sea area by using the ocean current field distribution model. Based on the video image, the ocean current of the target sea area can be finely monitored in a large range, the ocean current field distribution model can be used for accurately and quickly monitoring, and compared with the prior art, the method is more efficient.

The application discloses a reactor in-core component core upper plate underwater multifunctional detection device and a positioning method. The detection device comprises an omnidirectional moving chassis and an action mechanism detachably carried on the omnidirectional moving chassis. The action mechanism comprises a video lifting inspection module, a fuel positioning pin verticality inspection module, an in-situ ultrasonic inspection module of the fuel positioning pin and the split pin, and a pin hole emergency inspection module. The detection device is used for video imaging inspection of components in the core upper plate area through the video lifting inspection module, measures the inclination angle of the fuel positioning pin through the fuel positioning pin verticality inspection module, detects defects in the typical failure area of the split pin and potential cracks in the thread area and the light rod area of the fuel positioning pin through the in-situ ultrasonic inspection module of the fuel positioning pin and the split pin, and realizes in-situ emergency inspection of the pin hole of the core upper plate through the pin hole emergency inspection module, thereby solving the industry problem that there is a lack of comprehensive detection means in the core upper plate area.

The invention discloses an LED lamp strip video imaging control method and system based on pixel coordinate mapping, and relates to the technical field of visual image processing. The pixel coordinate mapping-based LED lamp strip video imaging control method comprises the following steps of S1, acquiring geometric structure data and operation performance data of an LED lamp strip, preprocessing the geometric structure data and the operation performance data, and constructing a bending management database; s2, according to geometric structure data of the lamp strip, analyzing a mapping deviation between a pixel coordinate and a physical coordinate in real time; s3, geometric structure data and operation performance data are obtained, and bending light attenuation analysis is carried out; s4, evaluating the thermal load state of the bending area according to the operation performance data and the thermal management data of the LED; and S5, displaying the operation performance data and the abnormal alarm information in real time through an interface, and realizing data closed-loop management and partition operation and maintenance tracing. The problems that the display precision of the bending area of the LED lamp strip is reduced, the brightness and the color are uneven, and the performance of the LED is degraded due to local heat accumulation are solved.

The invention discloses a road traffic sign updating method based on crowd source data, and belongs to the field of road traffic sign updating, and the method comprises the steps: processing vehicle-mounted video image data through employing a pre-trained deep learning model, recognizing the type and attribute of the road semantic information of a traffic sign in a video, and obtaining the space coordinate of the traffic sign; performing spatial registration on the identified information of the traffic signs and an open source road data map; calculating a sign similarity value of the traffic sign after space registration, and judging whether the newly added traffic sign replaces the existing traffic sign or the newly added traffic sign; and generating an inference map after the traffic signs are updated, and updating the open source road data map. According to the method, the updating of the road traffic sign information is promoted, the updating efficiency and accuracy of the map data are remarkably improved, richer and more timely semantic support is provided for applications such as automatic driving, and the accuracy of traffic sign positioning and the consistency of semantic information updating are ensured.

The invention discloses a partial discharge voiceprint multi-mode detection method, which comprises the following steps that voiceprint matrix detection nodes are set, on-site multi-mode signals are collected, and the voiceprint matrix detection nodes comprise an ultrasonic sensor, an infrared thermal imager, a temperature and humidity sensor and a camera; preprocessing the signal, extracting voiceprint features, and constructing a multi-modal feature vector; calculating three-dimensional coordinates of a partial discharge source, and performing spatial mapping verification by combining video imaging; and fusing the features and carrying out classification identification, and outputting a partial discharge type and a risk level. Through voiceprint matrix arrangement, temperature, humidity and video imaging data are combined, and the sensitivity and the anti-interference capability of partial discharge detection are remarkably improved. A noise reduction algorithm and a voiceprint feature fusion technology are adopted, so that complex environmental noise and real discharge signals can be effectively distinguished; the multi-modal data collaborative analysis can evaluate the insulation state of the equipment in real time, the false alarm rate is reduced to below 2%, and unmanned intelligent inspection of the transformer substation is supported.

The invention relates to a postoperative complication prediction method and device based on a two-way map neural network, and the method comprises the steps: collecting ICG video images before and after cerebrovascular bypass surgery, and obtaining the clinical feature data of a patient; preprocessing the collected ICG video image, extracting a blood vessel network by adopting an image segmentation algorithm, and generating corresponding blood vessel graph structures before and after bridging; extracting blood vessel features, blood flow dynamic features and clinical features from the collected ICG video images and clinical feature data, and constructing a multi-modal high-dimensional feature set; and taking the multi-modal high-dimensional feature set and the corresponding vascular graph structures before and after bridging as input, and generating a complication prediction score through a pre-trained prediction model based on a two-way graph neural network. Compared with the prior art, the method has the advantages that the multi-modal feature information is fused, the graph neural network structure is optimized, the model performance is stable, the accuracy is high, and the method has important clinical application value.

The invention provides an underwater alumen ustum quantitative alarm method, device and equipment based on an AI model and a medium, and relates to the technical field of water treatment and artificial intelligence. According to the method, the collected underwater alumen ustum video image is obtained in real time, the pre-trained AI target recognition model is adopted to perform semantic recognition and segmentation on the underwater alumen ustum video image, the alumen ustum area is extracted, the white noise part is reserved, and the semantic segmentation result is obtained; calculating density features and size features of alumen ustum in the image according to the semantic segmentation result; inputting the density features and the size features into a pre-trained model based on depth nonparametric fuzzy mapping, and classifying the alumen ustum distribution states to obtain alumen ustum state classification results; comparing the alumen ustum state classification result with a preset threshold value, and triggering an alarm if the alumen ustum state classification result exceeds the threshold value. The alumen ustum state can be accurately quantified, real-time alarm and process optimization are realized, and the water treatment efficiency and the automation level are improved.

The invention discloses a wide-spectrum high-resolution hyperspectral video imaging method and device, and the method comprises the steps: carrying out the feature extraction of a plurality of wide-spectrum aliasing wide-spectrum hyperspectral video frames captured by a wide-spectrum hyperspectral sensor in single exposure imaging, and obtaining a hyperspectral output feature; the method comprises the following steps: extracting features for panchromatic video frames of the same scene captured by a panchromatic sensor to obtain panchromatic output features, splicing wide-band spectrum hyperspectral video frames and the panchromatic video frames, and extracting features to obtain space-spectrum features; fusing the hyperspectral output feature, the panchromatic output feature and the space-spectral feature to obtain a final coding feature; the encoded features are decoded to obtain a high resolution hyperspectral video frame. The method aims at recovering spectral information of more wavebands from aliasing spectrums, the problems of spectral aliasing and the like are solved through fusion imaging, and high-resolution hyperspectral videos are obtained.

The invention provides a panoramic fusion and AI change monitoring method and system based on a video image, and belongs to the technical field of computer vision and geographic information processing.The method comprises the steps that firstly, a road network, land data and a double-spectrum video of a target area are obtained, and a double-spectrum panoramic image is generated through cradle head posture correction fusion; secondly, constructing a road network plot topological graph, generating a space risk probability matrix by using a space-time diagram neural network, and generating semantic masks in combination with land categories; then, performing weighted product operation on the risk probability, the semantic mask and the infrared and visible light features of the panorama to generate an enhanced feature matrix; and finally, comparing the characteristic matrixes in historical periods to calculate differential distribution, and locking an area exceeding a threshold value as a target change area, thereby realizing accurate monitoring based on spatial-temporal logic driving. According to the method, adaptive weighted sensing of high-risk area changes can be realized, and the problems of false alarm and missing alarm caused by traditional full-graph unified threshold monitoring are effectively solved.

The invention discloses a tobacco transplanter operation quality detection method based on remote sensing and deep learning, and relates to the technical field of agricultural machinery operation quality detection.The method comprises the following steps that the characteristics of seedling holes and missing planting holes are identified through a target detection model, the target detection model comprises a second-order attention mechanism SOCA module and a SimSPPF module, and the SimSPPF module is used for identifying the characteristics of the seedling holes and the missing planting holes; the second-order attention mechanism SOCA module captures correlation of multi-scale features in video images, the SimSPPF module fuses the multi-scale features, through two times of feature matching and background noise information elimination, seedling holes for effective sowing during operation of the tobacco transplanter are positioned and extracted from video data synchronously obtained during operation of the tobacco transplanter, and the seedling holes are used for seeding. According to the method, the miss-planting rate and efficiency of operation of the tobacco transplanter are tested by calculating the efficiency and miss-planting rate of effective seeding operation of the tobacco transplanter, so that the operation quality of the tobacco transplanter is quantitatively detected while the detection precision of seedling holes and miss-planting holes is improved.

The present application belongs to the technical field of robot control, and specifically discloses a railway inspection robot laser radar anti-collision and remote video linkage control method, aiming to solve the problems of low inspection efficiency, low sensor fusion degree and missing linkage mechanism in industrial scenarios. The method comprises: performing benchmark calibration and entering inspection line data through system initialization and parameter configuration; acquiring point cloud data by high-frequency dynamic scanning using a laser radar, and real-time matching of multi-level early warning thresholds to trigger linkage response; the power control unit executes brake or speed reduction operation according to the instruction, and resets the mode to resume work after confirming safety; the system also archives the full data of linkage events to support continuous optimization of the inspection plan. Through the deep coupling linkage of the laser radar and the video imaging module, the present application can realize all-weather, high-precision and high-safety autonomous operation of the inspection robot in complex high-dynamic environments, significantly improving the inspection efficiency and risk control level.

The present application relates to a wide-angle staring SAR video imaging method and apparatus based on trajectory error estimation. The method comprises: performing range compression on the original echo signal received by a wide-angle staring SAR, dividing the entire aperture into multiple overlapping sub-apertures, and performing coarse imaging of the sub-apertures using a BP imaging algorithm; performing coarse correction using a backprojection autofocusing algorithm based on the coarse image; imaging the sub-apertures using a BP imaging algorithm based on the coarse correction trajectory, dividing the imaging area into multiple sub-areas, estimating the trajectory error using a backprojection autofocusing algorithm and a weighted least squares method for each sub-area, and accurately compensating the coarse correction trajectory; registering the precisely compensated trajectories of different sub-apertures using a Kabsch algorithm, and performing video frame imaging using an autoregressive BP imaging algorithm based on the registered trajectory positions. This method achieves video frame imaging, autofocusing, and stability between video frames under any imaging model.

The invention relates to a wide-angle staring SAR (Synthetic Aperture Radar) video imaging method and device based on track error estimation. The method comprises the following steps: carrying out distance compression on an original echo signal received by adopting a wide-angle staring SAR, dividing a whole aperture into a plurality of overlapped sub-apertures, and carrying out coarse imaging on the sub-apertures by adopting a BP imaging algorithm; performing coarse correction according to the coarse imaging image by adopting a backward projection self-focusing algorithm; according to the coarse correction track, adopting a BP imaging algorithm to image the sub-aperture, dividing an imaging region into a plurality of sub-regions, adopting a backward projection self-focusing algorithm and a weighted least square method to estimate a track error for each sub-region, and performing accurate compensation on the coarse correction track; and registering the accurate compensation tracks of different sub-apertures by adopting a Kabsch algorithm, and carrying out video frame imaging by adopting an autoregressive BP imaging algorithm according to the registered track position. According to the method, video frame imaging, self-focusing and stability among video frames under any imaging model are realized.

1. Name of the product subject to this design: Projector (WH10). 2. Purpose of this design: For projecting text, patterns and video images. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: a 3D model.

The application discloses a kind of crowd flow prediction method, device, electronic equipment and nonvolatile storage medium.Therein, the method includes: determining the grid area corresponding to target scenic spot, wherein the grid area includes grid unit, each grid unit corresponds a scenic spot in target scenic spot;According to the video image corresponding to grid unit, determine the crowd space-time parameter of target unit in grid unit in first time period;Using target model, according to crowd space-time parameter, obtain the crowd flow of target unit in second time period, wherein the second time period is the next time period of first time period.This application solves the technical problem that the related art can not specifically predict the crowd flow of each scenic spot in the scenic area when counting the crowd flow of tourists in the scenic area, only based on the data of the entrance guard of the scenic area, resulting in low crowd flow prediction accuracy and poor tourist experience.

1. Name of the product in this design: Projector. 2. Purpose of this design: to project text, patterns, and video images. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: 3D view 1.

The invention discloses a video imaging adaptive three-dimensional scene synchronous rendering method and system, and relates to the technical field of 3D rendering, and the method comprises the steps: obtaining a rendering performance index of a video, and carrying out the preprocessing of the rendering performance index, and obtaining a rendering performance fluctuation index; dividing a current video scene into a plurality of resource regions, and determining the proportion of a high-density region and the proportion of a detail dense region; detail data are extracted from the synchronous rendering pipeline, and a material transition zone width interval and boundary adjustment parameters are determined; dynamically adjusting the computing resources by adopting a load balanced distribution method; and obtaining the original detail level and texture sampling density in the resource region, performing adaptive adjustment to obtain the optimized detail level and texture sampling density, and generating a balanced image output sequence. According to the method, the stability of the rendering frame rate in the complex dynamic virtual environment, the real consistency of picture details and the overall resource utilization efficiency are improved, and the rendering quality is improved.

The invention belongs to the technical field of fluorescence lifetime detection, and particularly relates to a fluorescence lifetime measurement method and system based on low-frame-rate video imaging. The method comprises the following steps: irradiating a to-be-detected sample by adopting an excitation light source, simultaneously collecting a video of a periodic luminescence attenuation process of the to-be-detected sample, and separating the video into a plurality of images with frame number marks; the excitation frequency of the excitation light source and the frame rate of video acquisition meet the following condition: FLED = Fcam + n, and n is a positive integer smaller than Fcam; all the images are converted into gray level images, and the average gray level value of light-emitting areas of the gray level images serves as a fluorescence signal intensity value; storing the fluorescence signal intensity value according to a frame number index, and screening out a signal attenuation sequence from the fluorescence signal intensity value; and fitting the signal attenuation sequence by using a least square method to obtain a fitting curve of the signal intensity value along with the time change, and obtaining the fluorescence lifetime of the sample to be detected from the fitting curve. According to the invention, the detection complexity and cost can be reduced, and the fluorescence lifetime of millisecond or even microsecond level can be measured.

Embodiments of the present application provide a motor vehicle parking lot scene map construction method, device and computer readable storage medium, the method comprising: constructing a global map coordinate system with a preset starting point of the parking lot as the coordinate origin, controlling the motor vehicle to drive from the preset starting point to the preset terminal point; in the process of driving the motor vehicle, generating a panoramic overhead view based on the video images collected by each vehicle-mounted camera; obtaining the current position coordinates of the motor vehicle at a predetermined period and constructing a local scene map of the motor vehicle based on the physical coordinates of the predetermined target in the panoramic overhead view; mapping the local scene map constructed in each period in the global map coordinate system according to the current position coordinates obtained in the corresponding period to obtain an initial global scene map; and excluding the repeated physical coordinates of the same predetermined target in the initial global scene map to obtain a target global scene map. The scene map constructed in this embodiment can be used to assist in selecting a parking space and to assist in realizing path planning.

1. The name of the design product: smart projector (Z6 Air). 2. The use of the design product: for projecting text, patterns and video images. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view.

1. The name of the design product: the support of the projector. 2. The use of the design product: the whole product is used for projecting text, patterns and video images, and the part of the product is used for supporting the projector. 3. The design points of the design product: the shape of the product represented by the solid line part. 4. The picture or photo that best shows the design points: the perspective view 1. 5. Other circumstances that need to be explained: the dotted line part in the figure is not the object of protection.

The invention discloses an ophthalmology video image processing method, device and equipment, and the method comprises the following steps: S100, collecting an ophthalmology video image at a preset frame frequency through an image collection unit, and transmitting each frame of ophthalmology image in the collected ophthalmology video image; s200, performing alignment and registration on the ophthalmological images based on a registration structure determined in a reference frame ophthalmological image to screen the ophthalmological images, and generating a static video image and a dynamic video image based on the screened ophthalmological images; and S300, presenting a static video image and / or a dynamic video image corresponding to a specified position based on the specified position in the reference frame ophthalmic image.

The application relates to the technical field of road network sensing, in particular to a highway sensing integrated system based on Internet of Things. The system comprises a server and various types of road network sensing devices, the road network sensing devices comprise laser radars, millimeter wave radars, high-definition cameras, environment detection units and infrared cameras arranged at intervals, the server comprises a weather identification module, which is used for acquiring video images captured by the high-definition cameras, and judging whether the road environment exists in a severe environment according to the video of the high-definition cameras; a device management module, which is used for controlling the high-definition cameras to be closed and the infrared cameras to be started when the weather identification module judges that the current road environment exists in a severe environment; an environment identification module, which is used for identifying the atmospheric transmittance of the current road according to the data measured by the environment detection unit; and the device management module is further used for controlling the laser radars to be started when the atmospheric transmittance meets preset conditions, and controlling the millimeter wave radars to be started when the atmospheric transmittance does not meet the preset conditions.

1. Name of the product of this design: Bicycle Recorder (Mei Rui ZJTY-M5). 2. Purpose of this design product: Auxiliary equipment for cycling, recording cycling tracks and audio and video images. 3. The key point of the design of this product lies in its shape. 4. The picture or photo that best illustrates the design points: Stereoscopic drawing 1.