100 results about "Occlusion detection" patented technology

Disclosed is a image processing apparatus and a method for controlling the image processing apparatus. The image processing apparatus according to an embodiment of the present disclosure may identify an object from an acquired image, determine whether the object is hidden by another object by using an aspect ratio of a bounding box of the detected object, and based on the object being hidden, estimate an entire length of the object based on coordinate information of the bounding box. Accordingly, the size information of the hidden object may be efficiently identified while a large amount of database is applied or resources of the apparatus is minimized. The present disclosure may be in connection with a surveillance camera, an automotive driving vehicle, an artificial intelligence module of at least one of a user terminal or a server, a robot, an augmented reality (AR) device, a virtual reality (VR) device, a device related to a 5G service, and the like.

The invention relates to the technical field of mine safety monitoring, in particular to an anti-shielding real-time deformation monitoring method and system for roof fall and wall caving disasters. The method comprises the following steps: extracting a bounding box and a mask of a discontinuous region from roof caving and rib spalling point cloud data, generating complete point cloud data, and analyzing a preliminary deformation index; extracting a track list of the shielding target, a prediction shielding area, a deformation trend and a deformation prediction value; in combination with the bounding box, the mask and the initial deformation index, obtaining a displacement vector and curvature change of the repaired missing region; and in combination with the trajectory list, the predicted shielding region and the deformation characteristics after compensation completion of the initial deformation index, obtaining a compensated and corrected displacement vector and curvature change, and further evaluating a deformation state and an early warning level. The method combines shielding detection, dynamic object tracking, multi-view fusion and deep learning completion to realize anti-shielding deformation feature extraction, time sequence trend prediction and accurate early warning, and provides reliable technical support for mine safety production.

The invention relates to a multi-source perception-based mechanical arm operation data acquisition system and method, the system comprises an isomorphic mechanical arm operation module, a multi-view visual image acquisition module, an optical motion capture module and a shielding detection and data fusion module, vision, pose and force sense data are cooperatively acquired through multiple sensors, and time-space consistency is synchronously kept by adopting hardware. The system has a multi-dimensional occlusion detection mechanism and can dynamically switch data processing strategies according to the occlusion degree: visual data is preferentially adopted when no occlusion exists, multi-sensor information is fused when partial occlusion exists, and force feedback compensation is predicted and introduced based on a dynamic model when complete occlusion exists. Physical feedback and visual perception are creatively combined, the problem of data missing of a traditional single sensor data acquisition system under the shielding condition is solved, more comprehensive and more reliable data support is provided for mechanical arm algorithm training and performance optimization, and the method is particularly suitable for complex operation scenes with shielding.

The invention discloses an unmanned aerial vehicle inspection optimal waypoint discovery method based on three-dimensional space shielding detection, and the method comprises the steps: 1) obtaining the latitude and longitude coordinates and height information of a to-be-inspected point, and loading a triangular patch model of a surrounding building or terrain; 2) generating a plurality of candidate observation waypoints with different heights and orientations above the to-be-inspected point; 3) calculating whether the sight line from the candidate waypoint to the ground inspection point is shielded by a triangular patch or not by using an R tree spatial index and a ray tracing algorithm; and 4) comprehensively considering the sight shielding condition, the observation distance and the observation angle, and selecting a waypoint which meets the non-shielding condition and has the optimal observation effect as an unmanned aerial vehicle inspection position. Compared with the prior art, the method has the advantages of being high in efficiency, low in cost and good in quality, the problem of viewpoint shielding in unmanned aerial vehicle routing inspection path planning under the urban complex environment is effectively solved, and the routing inspection efficiency and the data acquisition quality are improved.

A technical solution for monitoring operation of a medical delivery device such as a wearable patch pump for occlusion is provided that employs sensing pump motor current during at least one of a dispense stroke and an aspirate in a pump cycle. The solution can be implemented alone or in combination with other occlusion sensing methods that use one or more of pump measurement data such as pump stroke duration (e.g., duration of aspirate stroke or dispense stroke in a rotational metering-type pump or a reciprocating-type pump), end-stop or limit switch activation, and duration difference between aspirate and dispense strokes to detect occlusion. Accuracy of occlusion detection based on measured data in a fluid delivery device is improved by using dead band normalization of loaded measured data to unloaded measured data.

The invention discloses a three-dimensional human body posture estimation method and device based on multi-mode and occlusion perception, and relates to the field of computer vision, and the method comprises the steps: S1, obtaining a multi-mode video sequence comprising an RGB sequence, a depth sequence and an infrared sequence; s2, carrying out preprocessing to obtain a multi-modal video sequence with aligned data; s3, constructing a three-dimensional human body posture estimation model comprising a spatial-temporal feature extraction network, a shielding detection network, a time sequence coordinate classification module, a Z-axis depth prediction module and a three-dimensional coordinate splicing module; s4, training a three-dimensional human body posture estimation model by using the data-aligned multi-modal video sequence; and S5, performing three-dimensional human body posture estimation by using the trained model. According to the method, through RGB, depth and infrared three-mode fusion, X-axis and Y-axis coordinates are predicted by adopting a time sequence coordinate classification method of occlusion perception, and Z-axis depth prediction based on bucket separation and multi-mode and multi-resolution probability fusion is adopted, so that the problem of three-dimensional human body posture estimation in a complex occlusion scene can be effectively solved.

The application relates to the field of oral medicine diagnosis and discloses an AI-enhanced real-time occlusion detection system based on intraoral images, which comprises a multi-source intraoral image acquisition module, which is used for acquiring dynamic oral image data through a high-definition oral endoscope, recording the three-dimensional structure of a tooth surface in combination with a laser scanning device, and collecting the force distribution of an occlusion contact point through a pressure sensor array; the multi-source intraoral image acquisition module comprises a time stamp synchronization unit, which performs multi-source synchronization on the oral image frame sequence and the occlusion force distribution data by using a unified time mark; through the multi-source intraoral image acquisition module, the synchronous acquisition of dynamic images, three-dimensional structure data and occlusion force distribution is realized, and the time sequence consistency of the data is ensured through the time stamp mark. Compared with the acquisition mode of a traditional single data source, multi-source acquisition can comprehensively record the dynamic characteristics in the occlusion process, provide rich and accurate input for subsequent AI analysis, and avoid data omission or acquisition deviation.

The invention discloses a method for training a detection model for cerebrovascular occlusion detection and a related product. The method comprises the following steps: performing deboning operation based on CT perfusion imaging data to obtain target image data containing brain tissues and blood vessels; performing vascular occlusion region labeling on the target image data to obtain a three-dimensional occlusion region label; extracting a blood flow arrival time graph based on the CT perfusion imaging data; based on the target image data and the blood flow arrival time graph, extracting a blood vessel region feature volume after weighted fusion under blood flow arrival time gating; inputting the blood vessel region characteristic volume into the detection model to carry out cerebrovascular occlusion detection; and calculating a loss function based on the three-dimensional occlusion region label so as to train the detection model for cerebrovascular occlusion detection. By using the scheme of the invention, the accuracy, robustness and clinical applicability of occlusion detection can be improved.

The invention relates to the technical field of intelligent livestock management, in particular to an intelligent monitoring method and system for rumination behaviors of cattle individuals, and solves the technical problem of low monitoring accuracy in the prior art. The method comprises the following steps: acquiring cattle herd monitoring video data, and performing cattle mouth part identification on image frames in the cattle herd monitoring video data through a target identification model to obtain a cattle mouth area image in each image frame; performing shielding detection on the cattle mouth area image in each image frame, and screening out a target cattle mouth area image from the cattle mouth area images in each image frame according to an obtained shielding proportion; processing the screened target cattle mouth area image through an optical flow algorithm, and generating an optical flow field sequence representing cattle mouth movement; and inputting the optical flow field sequence into a preset classifier, judging whether the cattle is in a rumination behavior, and outputting a monitoring result of the rumination behavior.

The invention discloses a human body posture estimation method with occlusion detection correction and kinematics constraint optimization functions, which comprises the following steps: acquiring motion image data, detecting and marking unreliable key points of a target skeleton in the moving image data in each frame of static image by confidence analysis, time sequence information, space consistency and biomechanical prior information, so as to reserve reliable key points of the target skeleton in each frame of static image; correcting the reliable key point position of the target skeleton in each frame of static image based on polynomial fitting, a symmetry inference strategy and a human skeleton propagation strategy to obtain an initial overall skeleton; and introducing multiple physical constraints to construct a kinematics constraint function, and performing iterative optimization on the initial overall skeleton by taking minimization of observation deviation as a target to output human body posture estimation. The method provided by the invention can effectively solve the problems of key point loss, unreasonable structure and dynamic instability in complex scenes such as shielding and rapid movement.

The application provides a camera shielding detection method and device, electronic equipment and readable storage medium, and relates to the field of image recognition. The method comprises the following steps: acquiring a target image collected by a target camera, and calculating the light intensity of the target image; based on the comparison result of the light intensity of the target image and a preset light intensity, using a target model to analyze the target image, and generating an analysis result; wherein, the preset light intensity is the average value of the light intensity of the image whose camera shielding judgment is wrong; and the analysis result is used to indicate whether the target camera is shielded. The camera shielding detection method, device, electronic equipment and readable storage medium provided by the application can timely judge whether the camera is shielded under any light condition according to the image frame collected by the camera in real time, and improve the accuracy of shielding detection.

Systems and techniques are described herein for occlusion detection. For instance, a method for occlusion detection is provided. The method may include generating a plurality of voxels in a voxel space based on a point-cloud representation of a scene; generating an annotation point in the voxel space based on sensor data representative of an object in the scene; projecting a ray from a sensor position in the voxel space to the annotation point; and determining whether the annotation point is occluded based on the ray and the plurality of voxels.

This invention discloses a method and device for detecting the attitude of a spherical motor rotor. The method includes: developing a feature plate with three different visual feature points (first, second, and third) and fixing it to the top of the rotor output shaft; developing a visual detection system for the spherical rotor attitude, wherein when the rotor output shaft is located on the Z-axis of the northeast-northeast coordinate system, an image acquisition module is installed directly above the second feature point and calibrated; collecting and labeling typical and atypical spatial motion image datasets of the spherical rotor with three degrees of freedom; designing and training a network model suitable for detecting the real-time attitude of the spherical rotor using the YOLOv5s framework; the image acquisition module acquiring a frame of image in real time, using the network model to detect the coordinates of the three different visual feature points in the image, and calculating the attitude of the spherical rotor based on the detected coordinates and the geometric relationship of the rotor's spherical motion. This invention solves the problems of needing to reset and failure to detect feature points due to long-term occlusion in visual spherical rotor detection.

The application discloses the technical field of power grid operation, and particularly relates to a power grid operation site face recognition method based on deep learning, which comprises the following specific steps: S1: collecting face image pairs of power grid operation personnel and performing pretreatment to obtain a power grid operation personnel multispectral image pair dataset D1; S2: performing processing on any second face image pair P2 = <I''1, I'2> E D1 to obtain a power grid operation personnel multispectral image pair dataset D2; S3: constructing a face recognition model dynamic adversarial multi-modal network DAM-Net of the power grid site under the occlusion condition of the operation personnel, which is used for identity recognition of the operation personnel of the power grid operation site under the face occlusion condition; and S4: training and updating parameters of each layer of the DAM-Net network constructed in S3 to obtain a trained DAM-Net network. The DAM-Net of the application introduces a deformable convolution fusion submodule and a space-time attention mechanism submodule through a DODM, and has the advantages of being capable of significantly improving the accuracy and robustness of occlusion detection.

The present application discloses a LiDAR occlusion detection method and apparatus, a storage medium, and a LiDAR. The method includes: obtaining detected echo data, obtaining distance information of each point in the echo data, comparing the distance information with a preset distance range, and in response to the distance information being within the preset distance range, determining that the LiDAR is occluded. In the present application, it can be detected in real time whether the LiDAR is occluded, without affecting transmittance of the LiDAR or increasing manufacturing costs of the LiDAR.

The invention relates to a vehicle-mounted camera shielding detection method, a shielding detection system, shielding detection equipment and a computer readable storage medium. The method comprises the following steps: data preprocessing: acquiring a vehicle-mounted camera image, and dividing the vehicle-mounted camera image into data blocks according to equal division quantity after downsampling; feature extraction: for each data block, extracting basic features including brightness, contrast and histogram peak ratio, an edge feature being edge density, a complexity feature being superpixel set gradient relative change, and a pure color gamut feature being color ratio; block evaluation: according to the priorities of the basic features, the edge features, the complexity features and the pure color gamut features, correcting the edge features and the complexity features by using a brightness adaptive rule; performing mixed scoring: judging the blocking state of the data block, accumulating blocking scores in combination with a score block template, and comparing the blocking scores with a threshold value to obtain a blocking grade; and time sequence filtering: performing state transition judgment on the shielding level, filtering instantaneous interference and then outputting a detection result. According to the invention, high-robustness shielding detection in a complex vehicle-mounted scene can be realized.

The invention relates to a three-dimensional face high-fidelity texture generation method based on a multi-view high-definition image, and the method comprises the steps: constructing a three-dimensional face triangular mesh model through employing a camera fusion weight and an external parameter based on the cosine square of a view angle, and solving a texture mixed weight of each camera to a mesh triangular patch; the cylindrical UV expansion method is used for adapting to the geometrical characteristics of the human face, so that the texture stretching distortion can be obviously reduced; high-frequency detail reservation and low-frequency hue smooth transition are achieved through a frequency-band-divided texture fusion strategy, a high-quality texture source is optimized in cooperation with view angle cosine square weight and depth shielding detection, and fusion joints and detail dilution are avoided.

The application provides a kind of skeleton point occlusion detection method, device, equipment and storage medium. First, the position information of each skeleton point in human skeleton is obtained by acquiring color image, and the skeleton point set with connection relationship is obtained using the position information of each skeleton point. Then, the target region is obtained by region construction of human skeleton according to the connection relationship between each skeleton point. Finally, the occlusion detection result is obtained by judging the positional relationship between skeleton point and target region. That is, the application only needs to calibrate the target region according to the skeleton point with connection relationship, and can directly judge whether the detected skeleton point is occluded according to the positional relationship between skeleton point and target region. Therefore, compared with the prior art, the calculation amount of the application is small, and the occlusion of the skeleton point can be quickly and effectively judged by simple logic.

The application discloses a virtual occlusion detection and design method based on intraoral three-dimensional scanning and relates to the field of oral prosthetics. The application comprises the following steps: acquiring complete upper and lower dental arch data and static occlusion data of a patient in a static state; acquiring a dynamic motion trajectory of teeth by using the static occlusion data to correspond to the position of the teeth in a lower jaw motion in real time; combining the complete upper and lower dental arch data in the static state and the lower jaw motion trajectory to complete motion trajectory integration; drawing a boundary along a crown gum margin and an adjacent contact area in the static dental arch data to obtain a single tooth by segmentation; taking a crown cheek side as a common area, registering the segmented single tooth data to occlusion data one by one to obtain occlusion data after tooth-by-tooth registration; and designing a prosthesis based on the dental arch data and the occlusion data after tooth-by-tooth registration. The application can obtain accurate static and dynamic occlusion data and greatly improves the precision and efficiency of prosthesis design and production through automatic virtual occlusion detection and virtual adjustment.

The invention provides an unmanned aerial vehicle inspection shooting pose optimization method and system based on structure perception. The method comprises the following steps: determining a key detection area according to three-dimensional structure data of a detected object; generating a detectability constraint condition for the key detection area according to the imaging system parameters; generating a security constraint condition according to the security specification information; according to the three-dimensional structure data, shielding detection is carried out on a connecting line of the candidate pose and the key detection area, and a shielding constraint condition is generated; legal poses are sampled according to constraint conditions; selecting a representative pose set from the legal poses of the key detection areas according to the coverage amount, the pose number and the track length of the key detection areas; path planning is carried out based on the representative pose set, and an unmanned aerial vehicle inspection track is generated; the imaging quality of the key defect part is improved by utilizing a detectability index; shielding analysis is carried out based on a three-dimensional structure, and information dead angles are reduced; constraint conditions are explicitly unified, and risks caused by human experience are reduced.

The application discloses a human body occlusion detection method, a computer device and a storage medium. The human body occlusion detection method comprises the following steps: acquiring a to-be-processed image, and cutting out a human body image in the to-be-processed image; inputting the human body image into a neural network model, acquiring key point positions and semantic segmentation results of the human body image, acquiring a human body region segmentation image of the human body image based on the key point positions and the semantic segmentation results, the human body region segmentation image comprising a plurality of segmentation regions, each segmentation region having a corresponding pixel value; acquiring image pixel values of points corresponding to the key point positions in the human body region segmentation image, and judging whether the image pixel values are valid pixel values; if yes, acquiring effective pixel value region areas and region connectivity of each segmentation region, and judging whether each segmentation region is occluded based on the effective pixel value region areas and / or the region connectivity. The application can improve the reliability and accuracy of human body occlusion detection.

A method, apparatus, non-transitory computer readable medium, and system for image processing includes obtaining an input image and disparity information for the input image, where the input image depicts a first object and a second object and the disparity information indicates a depth of pixels in the input image and determining a first set of boundary pixels and a second set of boundary pixel from the input image. The first set of boundary pixels represents a first boundary between the first object and the second object and the second set of boundary pixels represents a second boundary between the first object and the second object that is separated from the first boundary. An occlusion label is generated based on the first set of boundary pixels, the second set of boundary pixels, and the disparity information, wherein the occlusion label indicates an occlusion between first object and the second object.

A system and method for vehicle occlusion detection is disclosed. A particular embodiment includes: receiving training image data from a training image data collection system; obtaining ground truth data corresponding to the training image data; performing a training phase to train a plurality of classifiers, a first classifier being trained for processing static images of the training image data, a second classifier being trained for processing image sequences of the training image data; receiving image data from an image data collection system associated with an autonomous vehicle; and performing an operational phase including performing feature extraction on the image data, determining a presence of an extracted feature instance in multiple image frames of the image data by tracing the extracted feature instance back to a previous plurality of N frames relative to a current frame, applying the first trained classifier to the extracted feature instance if the extracted feature instance cannot be determined to be present in multiple image frames of the image data, and applying the second trained classifier to the extracted feature instance if the extracted feature instance can be determined to be present in multiple image frames of the image data.

The invention provides a human body key point and time sequence feature-based personnel falling detection method and system. The method comprises the following steps of: sequentially performing frame extraction, shielding detection, generative completion and enhanced super-resolution processing on video stream data; a dynamic anchor frame adaptive YOLOv8 algorithm is adopted to detect a personnel target, and information such as boundary frame coordinates is output; tracking a target through an improved BoT-SORT algorithm to obtain an action track and target frame data; human body key points are detected based on a YOLOv8-Pose algorithm, and low-confidence key points are complemented in combination with kinematics constraints; the multi-dimensional features are fused and input into a TCN-Bi-LSTM mixed model, and a tumble detection result is output; the method improves the detection precision and the anti-interference capability through multi-link optimization, can effectively deal with shielding and target offset scenes, guarantees the monitoring stability, and is suitable for safety monitoring of various public and private scenes.

The application provides a kind of shelter detection method, device and related equipment.Therein, method includes: the edge extraction of the image to be detected of target monitoring area is carried out, obtains first set, wherein, first set includes the pixel point of the edge of image to be detected;According to the second set and first set of pre-acquisition, obtain first proportion information and second proportion information, wherein, second set includes the pixel point located at the edge of target monitoring area, first proportion information is the proportion of the edge of image to be detected in target monitoring area also edge, second proportion information is the proportion of the edge of image to be detected in image to be detected;In the case where first proportion information is less than first threshold and second proportion information is less than second threshold, determine that target monitoring area exists shelter.Combination of interframe detection and intradetection is used.The existence of shelter in target monitoring area is determined comprehensively, which can improve the determination accuracy of target monitoring area in shelter detection.

The invention relates to a method for detecting an occlusion in a fluidic channel of an infusion device, comprising: flowing a fluid within the fluidic channel during a first time period, wherein a flow rate of the fluid is set to a first flow rate; pausing the flow rate for a second time period; measuring a first pressure at a location along the fluidic channel during the second time period; after measuring the first pressure, increasing the flow rate to a second flow rate; pausing the flow rate for a fourth time period; after pausing the flow rate, measuring a second pressure at the location during the fourth time period; calculating, at a processor, a difference between the first pressure and the second pressure; and providing an indication that an occlusion is present based on a determination that a magnitude of the difference satisfies a threshold.

The application belongs to the technical field of computer vision and image processing, and discloses an occlusion detection method and system based on image registration and depth map and a storage medium, and the main idea is to solve the false detection problem caused by light change or local texture change. The main scheme comprises the following steps: matching a reference image and a to-be-detected image, calculating a homography matrix to align the images through RANSAC after filtering outliers, generating a three-channel residual image and converting it into a gray image. Morphological opening operation and binarization are performed on the gray residual image, and the connected regions with an area exceeding a threshold value are selected as candidate occlusion regions. Depth maps of two images are generated and aligned by using the homography matrix, the depth ratio is calculated after eroding the non-candidate regions, and the depth scales of the to-be-detected image and the reference image are unified. The average depth difference of the candidate regions in the two images and the average distance from the camera optical center plane are calculated, and if the depth difference exceeds a threshold value and the distance meets the conditions, the real occlusion is determined. The area proportion of the real occlusion region is counted, and if it exceeds a threshold value, the occlusion warning is triggered.

The invention provides a fire extinguisher life cycle management method and system based on the Internet of Things, relates to the technical field of the Internet of Things, and completes mobile identification and occlusion detection through image comparison, and generates a state mark and a warning. And then parallel processing is started, one path is used for analyzing the visible light image to evaluate the label and the rubber tube, and the other path is used for obtaining surface topography and corrosion data through phase calculation and three-dimensional reconstruction. Depth or compensation analysis is dynamically started in combination with moving and shielding states, a comprehensive score is generated by fusing double-process output, and finally graded monitoring and life cycle management of the fire extinguisher are realized through Internet of Things transmission, so that automatic and accurate monitoring and quantitative evaluation of the surface state of the fire extinguisher can be realized, and the fire extinguisher quality is improved. And intelligent maintenance and full-life-cycle fine management are supported.

Device (10) for occlusion detection in a hose line (11), in particular a medical pump unit (42), comprising a hose line section (12) and a sensor unit (14) with a detector (16), wherein the detector (16) is configured to detect at least one deformation value of the hose line section (12), medical pump unit (42) with such a device and method for controlling a medical pump unit.

To provide a monitoring device to monitor a status of a catheter, which may indwell in a vasculature of a patient.SOLUTION: A monitoring device may include a housing, which may include a distal end, a proximal end, and a fluid pathway extending through the proximal end and distal end. The distal end may include a connector configured to couple to a catheter assembly. The monitoring device may include one or more sensors disposed within the fluid pathway. The sensors may facilitate identification of an occlusion within the catheter assembly.SELECTED DRAWING: Figure 3D