204 results about "Body images" patented technology

The invention discloses a hydraulic engineering dam body crack detection method and system based on machine vision, and relates to the technical field of computer vision. A high-definition camera is used for shooting a dam body image, obtaining a sample data set, extracting feature parameters of different noise types, and constructing a feature database; filtering the current dam body image to obtain a first dam body image, enhancing the crack gray scale difference of the first dam body image, obtaining a second dam body image, segmenting the second dam body image, screening candidate cracks in the crack image, and identifying real cracks according to the edge features of the candidate cracks. According to the method, a feature database is constructed, a targeted dam body image processing flow is combined, a high-definition camera collection and automatic processing flow is used, filtering parameters are dynamically adjusted by constructing the feature database, gray level enhancement and precise segmentation are combined, real cracks are precisely recognized through edge feature analysis and comparison, and quantitative parameters are output; and a reliable basis is provided for dam body safety assessment.

The invention relates to the technical field of image style migration, in particular to a portrait-based controllable style migration and image art enhancement method and system, and the method comprises the steps: carrying out the preprocessing of an obtained content image, enhancing the contrast and definition of the image, and obtaining a preprocessed image; based on a preset image segmentation model, pixel-level semantic segmentation is carried out on the preprocessed image, and a figure main body image is output; obtaining style information, based on a preset style generation model, performing style migration on the character main body image according to the style information, and generating a stylized character image; obtaining a target style image, and fusing the figure image and the target style image based on a preset ComfyUI workflow to obtain a final processing image; the image processing method and the image processing device have the advantages that on the premise of high customization flexibility, the quality of the image after style migration is improved, and the coordination between the portrait main body and the background is improved.

The invention discloses a large model-based large yellow croaker growth stage feeding amount evaluation method and system, and belongs to the field of aquaculture, and the method comprises the steps: collecting underwater images of a fish pond in a plurality of shooting directions at the same time, and recognizing and segmenting a fish body image corresponding to each entity fish in each underwater image; determining the distance between an entity fish corresponding to the fish body image and a camera for collecting the fish body image, and extracting fish body appearance features of the fish body image; randomly selecting a fish body image from each shooting direction to form a fish body image association combination, and screening a second fish body image association combination from all possible fish body image association combinations according to the distance and fish body appearance features; and constructing three-dimensional point cloud data of the entity fishes according to the second fish body image association combination, fitting three-dimensional body shape parameters of the entity fishes through the three-dimensional point cloud data, and determining the final feeding amount of the fish school according to the three-dimensional body shape parameters of the entity fishes. According to the invention, the problem of low accuracy of the real-time feeding amount of the fish school can be solved.

The invention relates to a motion function data acquisition method and system based on human-computer interaction. The motion function analysis method is applied to a motion function analysis device and comprises the steps that in response to an initial position instruction of an abnormal object, initial motion analysis is conducted based on historical treatment data of the abnormal object, and initial motion data is presented; when the corresponding initial body image is detected, pose analysis is executed, and a body condition labeling box is displayed to a labeling person. After annotation confirmation is received, carrying out movement analysis in combination with annotation data and historical treatment data, and outputting action change data; and if the current body image corresponding to the current body image is detected, taking the current body image as a new initial image, and repeating the pose analysis and labeling process. And until an annotation stop instruction is received, the system summarizes each annotation and historical treatment data to carry out object function analysis, and motion function data of the abnormal object is generated. By adopting the method, the accuracy of understanding the current abnormal information of the abnormal personnel can be effectively improved.

The invention discloses a glass bottle defect detection method, which belongs to the technical field of defect detection, and comprises the following steps: labeling defect areas for all images and adding corresponding defect labels to obtain a first preprocessed image with the defect areas and the defect labels; respectively adopting corresponding pre-training models for a first pre-processed image in the bottle body image library, a first pre-processed image in the bottle opening image library and a first pre-processed image in the bottle bottom image library, taking the first pre-processed images as input, and outputting a predicted defect area and a predicted defect label, incremental learning is carried out on the corresponding pre-training models, and detection models corresponding to the bottle body, the bottle opening and the bottle bottom are obtained respectively; and respectively inputting the newly obtained images into the corresponding detection models to obtain corresponding defect labels, defect areas and confidence coefficients. The glass bottle defect detection method solves the problem that at present, different parts need to be detected at different times, and rapid detection of the glass bottle is difficult to achieve.

The invention discloses a commodity marketing picture and video generation method and device, equipment and a medium. The method comprises the following steps: receiving an input commodity image and description information provided by a user; carrying out preprocessing and main body segmentation on the commodity image to obtain a commodity main body image; based on the commodity main body image and the user description information, commodity content understanding is carried out through a multi-modal model, a structured commodity semantic tag is generated, and the commodity semantic tag comprises the category, the visual feature and the key attribute of the commodity; and on the basis of the commodity semantic label, creative content generation and automatic typesetting processing are carried out through a multi-modal model, and a commodity marketing image containing a background, an advertisement copywriting and decoration elements is generated. According to the method, the tedious process needing multiple stages, multiple tools and repeated manual intervention is integrated into a highly-automatic end-to-end process, the manufacturing efficiency of commodity marketing materials is improved, meanwhile, the requirement for professional skills of a user is lowered, and the consistency of the visual context, style and brand is guaranteed.

A system is provided.SOLUTION: A system, comprising: means for inputting height data; means for uploading a whole body image; means for selecting product data; means for transmitting the height data and the whole body image to a server; means for generating a list of available products and transmitting the list to a terminal; means for transmitting data of a selected product to the server; means for synthesizing an image of the product with the whole body image at an appropriate size and position to generate a fitting image; and means for transmitting the generated fitting image to the terminal.SELECTED DRAWING: Figure 1

Described are systems and methods to determine one or more regional body composition values for one or more regions of a body based on a processing of one or more two-dimensional images that include a representation of the body. Regional body composition values may include any of a fat tissue mass, a lean muscle mass, a bone mineral density, a skeletal muscle mass, etc., which may be determined for any one or more regions of the body, such as the right arm, left arm, right leg, left leg, trunk, android, gynoid, etc.

The invention discloses a vehicle seat adjusting device and method, electronic equipment and a storage medium, and relates to the field of vehicle seat control, and the device comprises an image collection module which is used for collecting a whole body image of a person in a vehicle; the visual algorithm processing module is used for receiving the whole-body image and judging the height of a person in the vehicle through a visual algorithm, and the visual algorithm comprises the steps that the whole-body image is preprocessed; recognizing a human body region in the image through a human body detection algorithm, wherein the human body detection algorithm is a convolutional neural network model based on deep learning; the visual algorithm processing module is used for extracting feature points in a human body area, the ergonomic data storage module stores an optimal seat angle database corresponding to different heights, and the seat adjusting control module is used for calling the corresponding seat angle in the database according to height data output by the visual algorithm processing module and adjusting the seat angle according to the height data. And the electric adjusting mechanism is controlled to execute an adjusting action.

This invention discloses a method and system for controlling submarine cable laying trajectory based on plow body state perception. The method includes: acquiring real-time state images of the plow body in the seabed operating environment to generate a plow body attitude distribution image; extracting feature point sets of the dynamic region of the plow body based on a preset plow body feature localization method; obtaining distribution information from the feature point set to the stable attitude region and correcting the feature point set; and comparing the plow body trajectory region by partitioning the corrected feature point set to obtain trajectory optimization information. The system includes plow body image processing, feature localization, feature correction, and partition comparison modules to generate stable or dynamic adjustment commands, achieving precise control of the plow body trajectory. This invention effectively optimizes the submarine cable laying trajectory by real-time perception of the plow body state, improving operational accuracy and stability.

The application relates to a kind of body image matching network assisted internal three-dimensional deformation field measurement method, belong to deformation measurement field.The application implementation method is: in reference body image, define calculation region and calculation voxel point;Using three-dimensional body image feature extraction network, key three-dimensional features are extracted simultaneously.Using three-dimensional feature matching network, key three-dimensional features are matched.From matched three-dimensional feature point pair, the feature point pair in the preset three-dimensional neighborhood range around each calculation voxel point is extracted, and the three-dimensional deformation initial value of the calculation voxel point is calculated when more than four groups of feature point pairs are judged;Less than 4 groups are directly assigned using the deformation initial value of other successfully calculated points with the spatial position of the calculation voxel point nearest to the interpolation or, as the three-dimensional deformation initial value of the point.Using three-dimensional reverse combination Gauss-Newton nonlinear iterative optimization method, high-precision internal three-dimensional deformation field measurement value is calculated, that is, internal three-dimensional deformation field measurement is realized.

The invention relates to the technical field of smart home and visual identification, in particular to an intelligent dressing mirror system based on non-inductive interaction and a clothes collecting method, and the intelligent dressing mirror system comprises a dressing mirror body which is used for displaying a whole-body mirror image picture of a user; the intelligent acquisition communication module is mounted on the dressing mirror body and is used for sensing a human body and acquiring an original image including a whole-body image of a user; and the cloud server communicates with the intelligent acquisition communication module and is used for analyzing and processing the acquired whole body image of the user and pushing a result to a mobile terminal of the user. Through the system architecture of hardware collection, cloud computing and mobile phone terminal interaction, the problems that an existing intelligent mirror is high in cost and poor in privacy, and traditional APP clothes input is tedious are solved.

A three-dimensional (3D) digital image of an individual patient marked with target therapeutic locations on a skin surface of the patient is used for locating those treatment locations on a patient's skin for fascial manipulation and other treatments. The 3D image may be obtained by merging an unmarked 3D digital patient model image converted from a 2D optical image with a “generic” musculoskeletal digital model having optimized target therapeutic locations distributed over a skin surface thereof. The generic musculoskeletal digital model may be obtained from a library of such images.

The invention provides a coaxial telecentric imaging tinplate can defect identification method and system, and relates to the technical field of defect identification, the system is composed of a coaxial telecentric camera assembly, a polarization multispectral light source assembly and an image processing and control unit, and can body images with constant magnification are obtained through a telecentric lens and coaxial illumination; a switchable cross-polarization visible light and near-infrared light source is used for synchronously collecting multi-modal images, and separation and difference are carried out on different polarization and wave band images to obtain a specular reflection component image, a diffuse reflection component image and a multi-spectral difference image. The image is divided into a character area, a pattern area and a bottom color area according to the format of the can body, comprehensive judgment is conducted through character comparison, a lightweight neural network and defect area connectivity analysis, automatic recognition of defects such as scratches, through printing and smudginess is achieved, and the accuracy and stability of appearance detection of the tin can on a high-speed production line can be improved.

The invention discloses a super-endurance multifunctional display device, system and application. The system comprises an image acquisition module, a weight data acquisition module, a processing module, a display module and a power supply module. The processing module calculates health index parameters based on the body image data and the weight data, calls an AI model to construct a 3D human body model, and generates reminding information when indexes are abnormal; meanwhile, responding to a scene selection instruction, recommending virtual clothes and ornaments from the electronic wardrobe, and displaying a fitting effect in a virtual scene; and multi-user interaction is supported, and other user terminals can be accessed for synchronous display and real-time discussion. The power supply module adopts at least two independently detachable battery units and an automatic switching circuit, monitors the electric quantity and automatically switches. According to the invention, precise health management reminding, immersive fitting experience, social interaction promotion and super-long battery life are realized.

The invention relates to the technical field of vehicles, in particular to a vehicle control system and a vehicle. The control system comprises an image acquisition module, a vehicle-mounted computing platform and a central domain controller, based on the control system, a body image of a vehicle target object is acquired, based on a built-in image processing module, the body image is recognized, and the height and the leg length of the target object are obtained; after a mapping relation model of the height, the leg length and the pedal height is called to determine the pedal height corresponding to the height and the leg length, a pedal control instruction is generated based on the pedal height and sent to a driving mechanism of a target pedal. According to the method and the device, the target pedal is automatically adjusted and unfolded to the matched height, so that personalized adaptation to passengers is realized.

The invention provides a visual field depth expanding method based on sparse scanning of a light field microscope, which comprises the following steps of: performing sparse scanning on a sample in X, Y and Z axial directions by utilizing a micro-lens array light field imaging system, enabling the overlapping rate between adjacent visual fields to be lower than a preset value, and acquiring multi-visual-field two-dimensional original light field data; performing pixel rearrangement and deconvolution three-dimensional reconstruction on the two-dimensional original light field image of each view to obtain a reconstructed three-dimensional body of each view; calculating the theoretical overlapping region width in the XYZ axial direction according to the sparse scanning step length, and carrying out consistency calibration on the overlapping region in the XYZ axial direction of the adjacent visual fields; and carrying out recursive fusion on the calibrated reconstructed three-dimensional body along the X, Y and Z axial directions to obtain a full-view-field and full-depth-of-view three-dimensional body image. According to the invention, not only can a larger imaging depth range be provided, but also the image definition at different depth levels can be ensured, and the inherent depth-of-field limitation of a traditional optical system is overcome.

The application discloses a tunnel boring machine space dynamic compensation seismic wave advanced detection method and system, comprising: receiving the reflection echo data of the current space position; compensating the reflection echo data according to the attenuation compensation factor of the current space position, wherein the attenuation compensation factor of the current space position is obtained by a trained neural network, and the prediction process comprises: after curve fitting of the attenuation compensation factor of the reflection echo data of the detected space position, the attenuation compensation factor of the next space position is predicted by using the trained neural network; the compensated reflection echo data is subjected to geological body imaging by using the equal travel time imaging method, and the geological body detection result is obtained according to the amplitude difference on the imaging profile. The space dynamic compensation algorithm of the mechanical wave attenuation is used to adaptively correct the attenuation compensation factor at the next tunneling surface, so as to compensate the received reflection echo data and enhance the identification ability of the reflection echo.

To analyze an image of a body to determine whether the image involves a level of change of a severity of a medical condition.SOLUTION: Methods, systems and computer programs for monitoring skin condition of a person. In one aspect, a method can include: obtaining data representing a first image, the first image depicting skin from at least a portion of a body of a person; generating a severity score that indicates a likelihood that the person is trending towards an increased severity of an auto-immune condition or trending towards a decreased severity of an auto-immune condition; comparing the severity score to a historical severity score, where the historical severity score is indicative of a likelihood that a historical image of the user depicts skin of a person having the auto-immune condition; and determining based on the comparison, whether the person is trending towards an increased severity of the auto-immune condition or trending towards a decreased severity of the auto-immune condition.SELECTED DRAWING: Figure 1

A garment size appropriate for a user is determined by obtaining a reference image of a human wearing a corresponding garment and obtaining nominal size data for the garment worn in the reference image. Body dimensions of the human depicted in the reference image are derived from the reference image and / or from another data source and are compared with the nominal size data of the garment. Corrections based on variations between the body dimensions and the nominal size data are used to generate corrected size data for the garment. On receiving a request for the garment in conjunction with user body data uploaded by the user, for example in a body image, the corrected size data is looked up for the requested garment. A size recommendation for the requested garment is conveyed to the user based on a comparison between the uploaded user body data and the corrected size data.

The invention discloses a method for automatically identifying cracks in the whole cracking process of high-compaction expansive soil. The method comprises the steps of preparation of a soil body, building of a drying model box, acquisition of crack images in the whole cracking process and crack identification and quantification processing. A crack image of the whole cracking process of the soil body is obtained at a short time interval; according to the method, a Python automatic file reading and data exporting function is utilized, and OpenCV fracture contour identification is combined, so that batch identification and quantification of fracture soil body images are realized, and data exporting and storage are automatically realized. The time, the water content, the fracture rate, the fracture length, the fracture entropy and the like can be recorded at the same time in combination with the change of the soil mass quality in the model box, and the fracture development condition of the whole soil mass cracking process in the two dimensions of time and water content is obtained. A crack image is analyzed by combining a PIV (particle image velocimetry) technology, micro-scale displacement of a soil body in the drying process is captured, the cracking position of the soil body is accurately captured before cracking, and the stage of crack development is distinguished according to the displacement direction.

A method for simulating a solid body animation of a subject includes retrieving a first frame that includes a body image of a subject. The method also includes selecting, from the first frame, multiple key points within the body image of the subject that define a hull of a body part and multiple joint points that define a joint between two body parts, identifying a geometry, a speed, and a mass of the body part to include in a dynamic model of the subject, based on the key points and the joint points, determining, based on the dynamic model of the subject, a pose of the subject in a second frame after the first frame in a video stream, and providing the video stream to an immersive reality application running on a client device.

The application relates to the technical field of vehicles, in particular to a handle control method and device of a vehicle, a vehicle and a program product, wherein the method comprises the following steps: acquiring a current position of a handle; collecting whole-body image information of a passenger; processing the whole-body image information to obtain contour information of the passenger; analyzing the contour information through a preset image processing algorithm to obtain height data of the passenger; obtaining a target position of the handle according to the height data based on a preset height adjustment strategy, and generating a target control instruction according to the target position; and adjusting the current position of the handle to the target position according to the target control instruction. Thus, the problems in the prior art that a fixed handle cannot help people with a lower height to get on and off the vehicle, and the difficulty of passengers to escape independently in an emergency is increased are solved, the handle has the characteristics of high adaptability and intelligence, the needs of different passengers can be met, the convenience and safety of passengers getting on and off the vehicle are improved, and the use experience of passengers is improved.

The invention discloses a train body image defect detection method based on multiple models, and the method comprises the steps: inputting a to-be-detected image and a standard image into a discrimination network, and outputting a defect existence probability through the discrimination network; if the probability value is in a preset interval, acquiring a dual-channel image, inputting the processed dual-channel image into a positioning network, and in the positioning network, performing multi-scale feature extraction on the dual-channel image by the backbone network to obtain a multi-scale feature map; the neck network firstly performs multi-scale feature fusion on the multi-scale feature map output by the backbone network to obtain a feature map I, then performs feature refinement on the fused feature map, and outputs a feature map II; and the detection head network classifies the feature map II, and predicts the position of a defect area and the probability value of existence of defects. According to the method, a double-model structure is designed aiming at the characteristics of large train body defect detection data volume and variable environments, so that the train body defects are quickly distinguished and positioned, and the accuracy and efficiency of the train body defects are improved.

The application discloses a kind of based on distributed vision's coating block piece closed loop inspection control system and method, it is related to automobile intelligent manufacturing and automatic quality detection technical field.The method includes the following steps: detecting vehicle information, and according to vehicle information and vehicle real-time position acquisition multi-angle vehicle body image, specifically, in the process of uniform speed of vehicle to be detected through detection area, according to the change situation of real-time position trigger distributed image acquisition;Multi-angle vehicle body image is analyzed using visual inspection model to block piece misloading, missing loading;According to the analysis result, man-machine collaborative closed loop inspection is carried out, wherein the vehicle that is unqualified to analysis result is manually reviewed, and manual review result is added to the training sample of visual inspection model to carry out model iteration optimization.The application uses distributed imaging to automatically detect misloading and missing loading of rough sealing block piece on automobile coating production line, and is deeply integrated with production execution system to realize closed loop quality control.

The present invention relates to a portable system and method for providing holistic wellbeing assessment to be performed. The system comprises a modular air-tight chamber built upon a plurality of vehicular chassis, watercraft and inflatable spaces with its internal air separated from external environmental air. An acoustic tactile and infra-red radiating floor and wall surface module (200). A mirror is embedded leaderboard and video consultation instructional display module (300). A health and nutrition assessment module (400); singular or plurality of retractable treatment and therapy couch module(s) (450) is contained inside a high air pressure and oxygen rich airtight chamber (800,). A health sensor data aggregator (740) and artificial intelligence (AI) based main controller (705) is connected cloud (790) to display the content. A health assessment module is integrated with plurality of interactive sensory and 3D stereoscopic vision camera arrays (420) and breathe analysis module (415). The health assessment module is integrated with facial scanning and 3D body imaging camera array module (8A) and the health assessment module with integrated breath analyser (415).

The invention relates to the technical field of organic fertilizer production, in particular to a machine vision-based vegetable decomposition degree online identification system for organic fertilizer production, which comprises a pile body image acquisition module, a permeation path construction module, a diffusion direction analysis module, a diffusion characteristic quantification module and a decomposition degree judgment module, the pile body image acquisition module is used for acquiring a surface image of a vegetable raw material pile body in an organic fertilizer composting area according to a preset time monitoring period and generating a timestamp index corresponding to an acquisition moment; according to the method, a decomposition permeation path chain is constructed, the physical process that vegetable decomposition liquid flows downwards along a pile gap under the traction of gravity is simulated, discrete dark spots are connected into link lines with physical significance, and the system can distinguish the decomposition depth by counting the number and length of the link lines, so that the decomposition efficiency is improved. Therefore, the identification result is more in line with the real biological reaction state in the vegetable heap.

The application discloses a kind of extrusion filling sand-prevention filling form monitoring test device and test method, device includes simulation formation sand box, the simulation formation sand box is connected with sand liquid mixing system, waste liquid recovery system, sand liquid mixing system, simulation formation sand box and data acquisition processing system are electrically connected, the simulation formation sand box includes heating jacket, the data acquisition processing system includes three-dimensional imaging system;The heating jacket is used to make simulation formation sand box in filling sand body consolidation, the three-dimensional imaging system is used to scan filling sand body, generates filling sand body three-dimensional image data.Utilize the device and method provided by the present application patent, can obtain intuitive three-dimensional filling sand body image, in combination reservoir physical property, can establish the influence law of extrusion construction parameter and reservoir condition to filling form, to evaluate extrusion filling sand-prevention effect further.

A smart image processing method and a device using same are provided. The method comprises: an image acquisition unit of acquiring an image for a specific area; an image conversion step of, when a person is detected in the acquired image, converting a body image of the person in the image into an image in which the person is wearing outer clothing; and a storage step of storing the converted image.

The invention discloses a satellite imaging jitter measurement system based on area array detection. The satellite imaging jitter measurement system comprises a camera management controller, a camera main body, an imaging / jitter measurement detector and a signal processor, wherein the camera management controller receives a primary power supply, a bus and a second pulse signal from a satellite, and manages and controls the camera main body, the imaging / jitter measurement detector and the signal processor; the camera main body is used for imaging a ground object to a rear focal plane of the camera main body; the imaging / jitter measurement detector is mounted on the rear focal plane of the camera main body, acquires an object optical image at the rear focal plane of the camera main body, converts the object optical image into an image electric signal through photoelectric conversion, and transmits the image electric signal to the signal processor; and the signal processor is used for receiving the image electric signal, processing the image electric signal and outputting the image electric signal to the data transmission compression encoder. The satellite imaging quality is effectively improved.