61 results about "Partial occlusion" patented technology

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 automatic welding method, device and equipment, a storage medium and a product, and relates to the technical field of welding automation. According to the method, the three-dimensional point cloud data and the two-dimensional image data of the welding area are collected, the three-dimensional point cloud data and the two-dimensional image data are fused, and the fused image is obtained. The rough welding area is determined through semantic segmentation based on the two-dimensional information contained in the fused image, and the target welding seam is determined in the rough welding area based on the depth information contained in the fused image, so that the precision and robustness of welding seam positioning are remarkably improved by utilizing the characteristics of the fused image; the system can stably operate in a complex factory environment with uneven illumination, strong reflection or partial shielding; and the dependence of the algorithm on environmental conditions is reduced, so that the algorithm is more suitable for the application scene of an actual manufacturing industry factory. And on the basis of more accurate positioning, the welding gun is controlled to weld the target welding seam, and the accuracy of automatic welding can be remarkably improved.

Systems and methods and devices are provided for treating conditions such as heart failure and / or pulmonary hypertension by at least partially occluding flow through the superior vena cava for an interval spanning multiple cardiac cycles. A catheter with an occlusion device is provided along with a controller that actuates a drive mechanism to provide at least partial occlusion of the patient's superior vena cava, which reduces cardiac filling pressures, and induces a favorable shift in the patient's Frank-Starling curve towards healthy heart functionality and improved cardiac performance. The occlusion device may include a lumen obstructed by a relief valve that may permit fluid flow through the occlusion device to release an excessive build-up of pressure.

A vascular occlusion catheter may be employed for at least partial occlusion of a target vessel. The vascular occlusion catheter system includes a proximal catheter shaft having at least one internal lumen, and a distal catheter shaft terminating in an atraumatic tip. An occlusion balloon is sealingly mounted to the proximal and distal catheter shafts. A central catheter shaft extends through the proximal catheter shaft, the occlusion balloon and into the distal catheter shaft. The proximal catheter shaft is secured to the central catheter shaft on a proximal side of the occlusion balloon and the distal catheter shaft is secured to the central catheter shaft on a distal side of the occlusion balloon. The occlusion balloon, the proximal catheter shaft and the distal catheter shaft have a greatest outer diameter of less than seven French (7 Fr) in an uninflated condition.

A control system for an occlusion catheter having a balloon includes a fluid reservoir containing a fluid and a fluid connector connectable to the reservoir and to the catheter to provide fluid communication therebetween. The fluid connector has a pressure sensor integrated therein. A pump is configured to move the fluid between the reservoir and the balloon via the fluid connector. A controller is in electrical communication with the pump and the pressure sensor. The controller is configured to: (i) receive data from the pressure sensor, the data being indicative of a pressure within the balloon, and (ii) in an autonomous mode of operation, control the pump to alter a size of the balloon by driving fluid from the reservoir toward the balloon or withdrawing fluid from the balloon, the control of the pump being based, at least in part, on the data from the pressure sensor.

Systems and methods and devices are provided for treating conditions such as heart failure and / or pulmonary hypertension by at least partially occluding flow through the superior vena cava for an interval spanning multiple cardiac cycles. A catheter with an occlusion device is provided along with a controller that actuates a drive mechanism to provide at least partial occlusion of the patient's superior vena cava, which reduces cardiac filling pressures, and induces a favorable shift in the patient's Frank-Starling curve towards healthy heart functionality and improved cardiac performance. The occlusion device may include a lumen obstructed by a relief valve that may permit fluid flow through the occlusion device to release an excessive build-up of pressure.

According to the figure portrait recognition method and device, the storage medium and the computer equipment provided by the invention, the image data including the to-be-recognized figure acquired from multiple angles of the monitoring area can be acquired, and then the facial features, the static features, the dynamic features and the spatial-temporal features related to the to-be-recognized figure in the image data from different angles are extracted respectively; therefore, even if the facial features of the to-be-recognized person are partially shielded or the posture of the to-be-recognized person is changed, the features (such as static features, dynamic features and spatio-temporal features) of other dimensions can still provide effective recognition information, and the recognition accuracy of the to-be-recognized person is improved. Therefore, normal operation of the recognition system in a complex scene is guaranteed, misrecognition caused by similar feature interference and missing report caused by shielding and posture change can be effectively reduced, the reliability and stability of the recognition system are effectively improved, and the recognition precision is improved.

An acoustic respiratory therapy device comprises a transducer interface comprising at least two acoustic transducers, the transducer interface for positioning the at least two acoustic transducers proximate a neck of a user, and a controller configured to control the at least two acoustic transducers to output acoustic waveforms that constructively interfere with one another at one or more target location(s) within a patient corresponding to at least a partial occlusion of the patient's airway.

The invention discloses a multi-angle template matching method based on gradient topology sparse coding. The multi-angle template matching method comprises the following steps of S1, extracting a gradient topology skeleton of a template image; s2, constructing and coding a skeleton sparse dictionary; s3, coefficient domain rotation mapping construction is carried out; s4, performing multi-angle matching and similarity calculation; and S5, result fusion and optimization. The invention relates to the technical field of computer vision and image processing, and has the beneficial effects that the features based on the gradient topology skeleton are insensitive to illumination variation, gray shift and noise interference can be effectively overcome, and the matching stability in a complex environment is improved. By constructing the coefficient domain rotation mapping relation, physical rotation reconstruction does not need to be carried out on the image, the calculation overhead of multi-angle matching is remarkably reduced, the search efficiency is improved, sparse coding is used for carrying out compact representation on the image structure, and the adaptive capacity to local deformation and partial shielding is enhanced.

Systems and methods and devices are provided for treating conditions such as heart failure and / or pulmonary hypertension by at least partially occluding flow through the superior vena cava for an interval spanning multiple cardiac cycles. A catheter with an occlusion device is provided along with a controller that actuates a drive mechanism to provide at least partial occlusion of the patient's superior vena cava, which reduces cardiac filling pressures, and induces a favorable shift in the patient's Frank-Starling curve towards healthy heart functionality and improved cardiac performance. The occlusion device may include a lumen obstructed by a relief valve that may permit fluid flow through the occlusion device to release an excessive build-up of pressure.

This application belongs to the field of vision system calibration technology, specifically relating to a target, a target center localization method, and a target calibration plate calibration method. The target provided in this application includes a circular positioning area and an annular recognition area; the annular recognition area surrounds the circular positioning area, which has a triangular mesh, comprising triangles or sectors symmetrically arranged around its center; the target center point is located at the centrally symmetrical point of the triangles or sectors; an annular coding band is provided inside the annular recognition area, comprising multiple arc-shaped coding strips; these arc-shaped coding strips are centrally symmetrical around the target center point. The target center of this application is the intersection point of the legs of multiple triangles in the triangular mesh. Even if the target is partially occluded, or the target center is occluded, the target center point can still be accurately located by connecting the intersection points of the legs of the unoccluded triangles in the triangular mesh.

Systems and methods are provided for treating conditions such as heart failure and / or pulmonary hypertension by at least partially occluding flow through the superior vena cava for an interval spanning multiple cardiac cycles. A catheter with an occlusion device is provided along with a controller that actuates a drive mechanism to provide at least partial occlusion of the patient's superior vena cava, which reduces cardiac filling pressures, and induces a favorable shift in the patient's Frank-Starling curve towards healthy heart functionality and improved cardiac performance. The system may include sensors to determine the degree of occlusion of the superior vena cava. The occlusion system may be used to reduce volume in a heart and facilitate a cardiac procedure. The occlusion system may be used to relieve an overloaded chamber during and / or after deploying a VAD.

The application discloses a panoramic depth high dynamic range imaging system and method based on compound eye structure, relates to the technical field of computational imaging and image processing, and synchronously collects and multi-scale motion estimation ensures the time sequence consistency between sub-images, effectively reduces the splicing dislocation and ghosting caused by the rapid movement or partial occlusion of an object, and improves the stability of a dynamic scene; an adaptive HDR fusion mechanism based on exposure difference and local features preferentially retains high-contrast unsaturated region details through intelligent weight distribution, overcomes the overexposure and underexposure problems under backlight or light mutation, and makes the output image naturally smooth in the bright-dark transition area; in addition, multi-scale depth synthesis and edge perception filtering work cooperatively, enhances the depth estimation accuracy of a low-texture area, avoids depth jumping and edge blurring, and guarantees the overall definition of the panoramic depth image; meanwhile, rolling shutter correction and space-time interpolation compensation further reduce dynamic ghosting and noise interference.

Systems and methods are provided for treating conditions such as heart failure and / or pulmonary hypertension by at least partially occluding flow through the superior vena cava for an interval spanning multiple cardiac cycles. A catheter with an occlusion device is provided along with a controller that actuates a drive mechanism to provide at least partial occlusion of the patient's superior vena cava, which reduces cardiac filling pressures, and induces a favorable shift in the patient's Frank-Starling curve towards healthy heart functionality and improved cardiac performance. The system may include sensors to determine the degree of occlusion of the superior vena cava. The occlusion system may be used to reduce volume in a heart and facilitate a cardiac procedure. The occlusion system may be used to relieve an overloaded chamber during and / or after deploying a VAD.

The invention discloses a constructional column steel bar position offset prediction method and system based on machine learning, and the method comprises the steps: introducing BIM space prior, so as to make up for the initial detection deviation caused by insufficient image information, and enabling a model to carry out the effective feature extraction and initial recognition under the conditions of complex light and partial shielding; further, relation correction and structure optimization are carried out on the candidate steel bar objects by utilizing a topological graph template, so that the accurate identification capability of the seriously shielded steel bars and the integrity interpretation of the whole steel bar structure are remarkably improved; subsequently, the three-dimensional offset vector of each steel bar is accurately calculated based on the three-dimensional offset vector, so that the detection accuracy and reliability are greatly improved, the construction engineering quality control level is remarkably improved, the structure safety is guaranteed, the rework cost is reduced, and the method has remarkable engineering practice value.

The application discloses a local face age estimation method based on multi-channel learning in a shielding scene and relates to the technical field of age estimation. The application uses a method of simulating shielding, generates partially shielded face images and corresponding shielding labels based on a face age image dataset, trains a shielding detector to detect grids with shielding, proposes an age feature extraction model based on multi-channel learning, divides a to-be-detected image into grids, inputs the to-be-detected image into a feature extraction module, and extracts features of the grids. In combination with the shielding detector result, a feature fusion module is used to fuse features of the grids that are not damaged by shielding, obtain final age features, and further obtain an estimated age value. The application can accurately estimate the face age under a local shielding condition, meets the robustness and accuracy requirements of a face age estimation task in a local shielding scene, and solves the problem that the age estimation is inaccurate due to local shielding in the prior art.

The application provides a multi-image complementary information tracking method with a dynamic activation mechanism, comprising the following steps: tracking a target by using a built network to obtain a tracking result, wherein the built network comprises a Transfomer feature extraction network with a multi-head attention module to calculate a mixed template feature and a scene perception activation module, a multi-view mutual information module, and a head prediction network with an added bounding box prediction branch based on a classification branch and a regression branch.The multi-image complementary information tracking method of the application has better performance under the premise of meeting the real-time running speed in the face of changes in viewing angle, similar object interference, partial occlusion and rapid motion, and can effectively improve the tracking success rate and accuracy.

The invention relates to the technical field of computer vision and target detection, in particular to an object detection method for shielding a small target, and the method proposes a Z-shaped cutting method which can effectively manufacture diversified local shielding situations while retaining background context information, thereby remarkably enhancing the detection robustness of a model to a shielding target. And meanwhile, aiming at a YOLOv11n model architecture, a heterogeneous bottleneck module and a self-adaptive attention convolution fusion module are introduced. According to the method, three-dimensional simulation data generation, image occlusion simulation enhancement and target detection network structure improvement are comprehensively utilized, so that the performance of a detection model under the conditions of complex backgrounds, multi-scale changes and partial occlusion is improved; the problem that the detection precision is remarkably reduced due to the fact that the target size is small or shielding exists in the target detection task is solved.

The present application belongs to the field of visual tracking technology, and discloses a kind of processing existing partial occlusion flexible linear object visual tracking method, based on RGB-D camera obtains color image and depth image data, from first frame image, by mask segmentation, skeletonization processing operation generates initial state point, in each subsequent frame, object point cloud is generated by mask in conjunction with depth image;Then, the density of its surrounding current point cloud is counted, and the state point is marked as "visible" or "occlusion";By establishing the analytical model based on the spatiotemporal continuity of flexible linear object, the closed form solution of the occlusion position is derived, and the iterative optimization process of the occlusion position is eliminated, thereby reducing the computational complexity and achieving efficient real-time tracking;Meanwhile, using the inherent spatiotemporal geometric evolution law of flexible linear object, a position estimation model that can be directly analytically solved is constructed, avoiding the stability risk brought by iterative optimization, and significantly improving the reliability and tracking stability of the occlusion position estimation.

The application discloses a kind of non-contact heart rate detection methods for face has sheltered scene, steps are as follows: input training video, face picture sequence is intercepted by face recognition;Training is based on the three-dimensional residual neural network of block;Extract the block weight based on correlation coefficient;Extract the block frequency domain feature clustering center;Input real video, face picture sequence is intercepted by face recognition;Extract the block depth feature by the three-dimensional residual neural network of block based on the training;Extract the block weight based on clustering;Extract block detection heart rate, the block weight based on correlation coefficient and the block weight based on clustering are weighted summation, obtain final detection heart rate.The application assigns different weights to the heart rate detection results of different facial regions, overcoming the problem of accuracy decline in non-contact heart rate detection method under the scene of partially occluded face.

The invention relates to the technical field of machine vision algorithm expansion and application, and discloses a robot medicine dispensing method based on feature extraction and violent matching, which is suitable for medical robots, automatic pharmacies and other scenes and can realize efficient and stable medicine identification and configuration in a low-computing-power environment. According to the method, the ORB feature extraction algorithm and the violence matching algorithm are utilized, rapid and accurate identification of drugs is achieved, dependence on GPU computing power is reduced, environmental adaptability is improved, and embedded equipment is adapted through lightweight design. According to the method, high recognition accuracy can still be kept in complex environments such as illumination variation and partial shielding, and the method has the remarkable computing power advantage, environment robustness and system reliability.

The invention belongs to the technical field of visual tracking, and discloses a visual tracking method for processing a partially-shielded flexible linear object, which comprises the following steps of: acquiring color image and depth image data based on an RGB-D camera, generating an initial state point from a first frame of image through mask segmentation and skeletonization processing operation, and in each subsequent frame, generating an initial state point from a second frame of image through mask segmentation and skeletonization processing operation; generating an object point cloud by combining the mask with the depth image; then, counting the density of current point clouds around the state point, and marking the state point as visible or shielded; an analytical model based on space-time continuity of a flexible linear object is established, a closed form solution of a shielding position is deduced, and an iterative optimization process of a shielding state point position is eliminated, so that the calculation complexity is reduced, and efficient real-time tracking is realized; and meanwhile, the inherent space-time geometric evolution law of the flexible linear object is utilized to construct a position estimation model which can be directly analyzed and solved, so that the stability risk caused by iterative optimization is avoided, and the reliability and tracking stability of shielding position estimation are remarkably improved.

The present invention proposes a semi-supervised MRI brain tumor segmentation method based on a contrast-guided diffusion model, belonging to the field of image segmentation. In step S1, the T1 sequence data of the BraST2018 dataset is sliced, and the slice data without tumors is partially occluded; in step S2, pairs of lesion and healthy image data are generated, and the minimum bounding rectangle occlusion is constructed using the brain tumor sample mask, and the lesion area is restored to healthy tissue; in step S3, through the data pairs obtained in S2, the contrast information is used to guide the diffusion model to denoise and generate lesion labels. Thereafter, pre-training is performed with labeled data, and pseudo-labels are generated for unlabeled data through the pre-trained model, and then brought into the model together with the labeled data for the re-training process; in step S4, the structural contrast loss is used to improve the information mining ability of the model when the confidence of the pseudo-labels is insufficient; in step S5, only a small amount of labeled data is used for training and validation. The present invention realizes the lesion segmentation of MRI brain tumors by constructing a semi-supervised segmentation method based on a contrast-guided diffusion model, on the premise of only requiring a small amount of labeled data. This method solves the problem that traditional deep learning segmentation methods overly rely on a large amount of labeled data and improves the segmentation performance of the model under the condition of a small amount of labeled data.

The invention discloses an automobile blind area early warning method and system based on image recognition and a storage medium, and relates to the technical field of automobile blind area recognition based on Internet security. The automobile blind area early warning method based on image recognition comprises the following steps of data acquisition, complete shielding evaluation, partial shielding detection and partial shielding evaluation. According to the method, the image data is obtained by performing image preprocessing on the blind area image, complete occlusion judgment is performed on the image data and the reference data interval, a first-level early warning measure is taken, the partial occlusion influence coefficient is obtained according to the image data and the reference image data, and whether partial occlusion evaluation is executed or not is judged according to the partial occlusion influence coefficient and the partial occlusion threshold value. And obtaining all partial shielding influence coefficients in a preset time period to obtain a partial shielding similarity coefficient, and judging whether to take a secondary early warning measure according to the partial shielding similarity coefficient and a similarity threshold value, thereby achieving the effect of improving the accuracy of the image-based automobile blind area early warning, and solving the problem of insufficient image analysis in the automobile blind area early warning in the prior art.

The embodiment of the invention provides an electronic image stabilization method, which is used for processing visible light video data of an airborne photoelectric hanging bin, and comprises the following steps of: 1, acquiring video sequence basic information; step 2, feature point detection and motion estimation; step 3, performing abnormal processing on the motion model; step 4, motion trail smoothing processing; 5, image stabilization transformation and post-processing are carried out; and step 6, outputting a result. Aiming at visible light video data of an airborne photoelectric pod, various forms of jitter motion can be accurately captured and compensated through multi-scale feature point tracking and intelligent motion estimation. Compared with a traditional method, the method shows higher precision and stability when a complex motion mode is processed. Especially in scenes with slight motion blur, illumination variation or partial shielding, the method can still keep reliable image stabilization performance. The smooth processing of the motion trail enables the finally output video to eliminate uncomfortable jittering and maintain the intentional motion of the camera, thereby conforming to the visual perception characteristics of human beings.

Systems and methods and devices are provided for treating conditions such as heart failure and / or pulmonary hypertension by at least partially occluding flow through the superior vena cava for an interval spanning multiple cardiac cycles. A catheter with an occlusion device is provided along with a controller that actuates a drive mechanism to provide at least partial occlusion of the patient's superior vena cava, which reduces cardiac filling pressures, and induces a favorable shift in the patient's Frank-Starling curve towards healthy heart functionality and improved cardiac performance. The occlusion device may include a lumen obstructed by a relief valve that may permit fluid flow through the occlusion device to release an excessive build-up of pressure.

The invention discloses a three-dimensional face reconstruction and emotion analysis method, device and equipment based on text guidance, and the method comprises the steps: obtaining the face image information of a human body, carrying out the preprocessing and labeling, and constructing a training set; and training the three-dimensional face reconstruction model by adopting the training set based on text guidance, inputting a to-be-analyzed face image into the trained three-dimensional shape model to obtain a face three-dimensional grid, and inputting the face three-dimensional grid into the emotion analysis model to judge the face emotion category. According to the method, the attribute matrix generated by the natural language and the image features are jointly coded and input to the three-dimensional reconstruction framework, so that the geometric reconstruction precision in complex scenes such as face blurring, local shielding or violent / subtle facial expression change can be remarkably improved; therefore, the problem of reconstruction failure or feature loss of a traditional method under a non-ideal image condition is effectively relieved.

The invention discloses a mobile robot vision book checking method and system, and the method comprises the steps: obtaining a spine image, recognizing a book name text in the spine image, and obtaining a book name recognition result; determining at least one word to be corrected based on the book name recognition result and a pre-constructed candidate word bank; performing recall operation on the word to be corrected to obtain a candidate set; calculating the comprehensive score of each candidate word in the candidate set; and based on the comprehensive score, selecting the candidate word with the highest comprehensive score to replace the word to be corrected so as to output a corrected book name. After the spine image is obtained and the book name text is recognized, the word to be corrected is determined based on the pre-constructed candidate word bank, and then intelligent correction of the book name recognition result is realized through the processes of candidate word recall, comprehensive score calculation and optimal candidate word selection. Text recognition errors caused by factors such as spine deformation, non-standard fonts and partial shielding in the visual recognition process are effectively overcome, and the accuracy and robustness of book name recognition are remarkably improved.

A method for detecting abnormal human behaviors based on improved SSD, which trains and evaluates the SSD network model on a preprocessed dataset of abnormal human behaviors. It improves the problems existing in the SSD network model, including poor real-time performance of the model due to a large number of parameters and low detection accuracy caused by the inability to detect abnormal behaviors with partial occlusion. The lightweight network MobileNetv2 is used as the feature extraction network of the SSD model, and a deformable convolution module is embedded to construct the convolutional layer to enhance the receptive field. On this basis, the output feature map is enhanced through the coordinate attention mechanism. By learning the context relationship, it can capture the long-range dependence between spatial positions, and predict the occluded part based on the unoccluded part to effectively improve the occlusion problem. The abnormal behavior datasets targeted by the present invention all occur in a natural state, can accurately detect the categories and positions of abnormal human behaviors, and at the same time, the detection of the model for partial occlusion situations existing in the dataset scene is improved, having good application prospects.