46 results about "Camera array" patented technology

A camera array system featuring a plurality of camera clusters attached to a plurality of multi-prong stabilized mounting plates arranged in a split-rig configuration, with the mounting plates configured for mounting the camera clusters onto a moving vehicle.

The application provides a plate tail intelligent grading equipment and method based on visual guidance, and the core is that through integration of multi-view visual perception, adaptive grabbing, digital twin and cloud-edge collaborative control technology, full-process intelligent management of plate tail from warehousing, grading storage to on-demand use is realized; multi-view images of the tail are collected by a camera array, three-dimensional point clouds are reconstructed through a stereo matching algorithm, and morphological characteristic parameters of the tail are extracted; with the help of digital twin technology, a virtual model of each tail is generated and synchronized, a stacking strategy is optimized based on a genetic algorithm, and space utilization is maximized; when a use request is received, the system can perform virtual cutting pre-performance in the digital twin environment, accurately match the demand, and use the stacked tail through the temporary storage-backfilling mechanism; finally, through the cloud-edge collaborative platform, visual monitoring and global scheduling optimization of the inventory and equipment state are realized, and the tail management efficiency and material utilization are significantly improved.

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).

A method and system for capturing images of scenes, such as medical scenes, and tracking objects within those scenes. To provide. [Solution] The camera array includes a support structure having a center and a depth sensor mounted on the support structure close to the center. The camera array may further include a plurality of cameras mounted on the support structure radially outward from the depth sensor and a plurality of trackers mounted on the support structure radially outward from the cameras. The cameras are configured to capture image data of the scene, and the trackers are configured to capture position data of tools in the scene. The image data and position data can be processed to generate a virtual view of the scene, including a graphic representation of the tools at the determined positions.

This invention discloses an online detection system for airbag coating defects based on machine vision and deep learning, belonging to the field of airbag coating detection technology. It includes: a multispectral imaging module containing visible and infrared light sources, forming a ring-shaped multispectral light source array for acquiring visible and infrared spectral images of the airbag coating surface; an FPGA-accelerated lightweight deep learning model, including adaptive convolution kernels and channel-parallel computing modules, achieving real-time inference at <50ms / frame; an adaptive illumination control module integrating an ambient light sensor and deep learning model output, adjusting light source parameters in real time through a closed-loop control algorithm; and a multi-angle imaging and image fusion module, including a ring camera array and a compressed sensing encoder, for acquiring multi-angle images of the airbag surface and generating a 3D defect distribution map. This invention achieves high-precision, high-speed, and highly robust online detection of minute defects in airbag coatings.

A system for generating a real-time object-focused video using minimal camera arrays with pre-computed sports-field-optimized spatial mapping. The system positions virtual cameras to maintain tracked objects in focused, straight-ahead orientations while supporting one-dimensional movement between two cameras using geometric interpolation and two-dimensional movement within three-camera triangular configurations using barycentric coordinates. Computer spatial mapping with discretized depth information optimized for fast-moving object tracking in sports environments eliminates real-time depth calculation overhead, avoiding latency bottleneck and enabling ultra-low latency processing suitable for live sports broadcasting. The system includes predictive camera set switching using mathematical positioning variables, multi-object tracking capabilities with distributed processing frameworks, and intelligent 2D occlusion handling optimized for broadcast video output with parallax-induced occlusion management. Video synthesis techniques including adaptive geometric transformation, and multi-resolution image processing achieve rapid processing performance for live broadcasting applications while preventing discrete camera switching artifacts through continuous interpolation coefficients that eliminate abrupt perspective transitions.

This invention relates to the field of action recognition technology, and in particular to an artificial intelligence violation detection method and system for pull-up tests, including pre-test data acquisition, multimodal fusion detection, and mechanical auxiliary verification. Compared to existing technologies that primarily rely on video stream data for counting and detection, which suffers from difficulties in accurately identifying concealed violations such as leveraging or explosive force, and are susceptible to misjudgments due to environmental factors such as occlusion and lighting changes, this invention achieves simultaneous acquisition and in-depth analysis of video stream data and mechanical change curves throughout the testing process through the collaborative work of a high-definition camera array and a high-precision mechanical sensor. It establishes a strict temporal correspondence and mutual verification mechanism between the two, ultimately completing automated comprehensive evaluation based on a multi-dimensional evidence chain. This effectively overcomes the limitations of pure visual analysis, significantly improves the accuracy of violation action recognition, and greatly enhances the system's environmental adaptability.

The application provides a bridge erecting machine intelligent construction system and method fusing multi-vision and multi-sensing array, and relates to the technical field of intelligent bridge construction, which comprises a multi-vision unit, a multi-source sensing unit, an edge computing and fusion processing unit, a central intelligent control decision unit and an execution mechanism driving module. Three-dimensional visual information is collected by a spherical camera array and a laser radar, combined with multi-source sensor data such as inclination, GNSS, displacement and pressure, real-time three-dimensional reconstruction is realized by using a VGGT network and a 3D Gaussian Splatting technology, and target recognition and positioning are carried out based on a YOLO algorithm and multi-view fusion. The central control unit carries out path planning, collision detection and LQR closed-loop control according to the reconstructed model and the recognition result, and drives the bridge erecting machine to complete automatic construction operation. The application improves the construction precision, safety and intelligent level of the bridge erecting machine in a complex environment.

This invention discloses a precision detection method and system for surface defects in metal strips, relating to the interdisciplinary fields of mechanical engineering and machine vision. The method includes: synchronously acquiring multi-band images using a multispectral light source and an industrial camera array; establishing a spatiotemporal synchronization model based on encoder speed signals and performing sub-pixel-level image registration to correct motion distortion; adaptively fusing multispectral images based on a material-spectral response database to enhance the signal-to-noise ratio of micro-defects; employing a lightweight deep learning model to achieve pixel-level defect segmentation and classification; and extracting defect geometric parameters and automatically classifying them using a process tolerance library. This invention aims to solve the problems of narrow material applicability, severe image distortion under high-speed motion, low micro-defect detection rate, and complex system deployment in existing technologies. It achieves high-precision, high-speed online detection of non-ferromagnetic metal strips, significantly improving the sensitivity to micron-level defects, system robustness, and ease of deployment.

The application discloses an unmanned garbage collection method based on multi-sensor fusion and edge intelligence, and belongs to the technical field of garbage treatment. The method comprises the following steps: collecting environmental visual information by using a high-definition camera array, constructing a three-dimensional point cloud map by using a laser radar and performing obstacle ranging, and fusing data collected by each sensor; performing real-time inference on multi-source data by using a deep learning model, and identifying the category, material characteristics, position coordinates and confidence of road surface garbage; integrating perception data and garbage identification results, overall planning global task scheduling, and generating a globally optimal cleaning path; a flexible grabbing end effector automatically switches the grabbing mode according to the garbage category; and a garbage bin automatic door is automatically opened when the mechanical arm is detected to be close. The application has the integrated functions of autonomous navigation, accurate target identification, flexible grabbing and garbage classification, and significantly improves the automation level and operation efficiency of urban environmental sanitation operation.

A method for measuring a shape of a reflector surface of a heliostat at night using a bright star at different elevation and azimuthal settings according to an embodiment of the current invention includes setting the heliostat in fixed orientation such that aberrated and overlapping star images formed are translated due to Earth's rotation in a translation direction across the heliostat array receiver; viewing images of the bright star using a fixed array of cameras placed at or near an array receiver of the heliostat, wherein each camera of the fixed array of cameras has a large aperture lens, and simultaneous exposures are made quickly enough and repeated for long enough, so that, as they translate past the cameras, the aberrated star image is fully sampled in two dimensions, and wherein every point on the reflector surface of the heliostat appears in one or more of the recorded images as being bright from reflected starlight; and processing the recorded images from the fixed array of cameras with a data processor to obtain the surface shape by integration of the surface slopes.

This invention discloses a multimodal grading method for seedless watermelons that integrates appearance texture and single-fruit weight. The method includes: simultaneously capturing images of the watermelon placed on a weighing device using a circular camera array and a top-view camera to obtain multi-view image sequences and single-fruit weight data; reconstructing a three-dimensional surface point cloud of the watermelon based on the image sequence and fitting it as a hyperellipsoidal model; mapping the three-dimensional surface texture to a two-dimensional texture map and simultaneously generating a distortion-corrected weight map; using this weight map to weight the two-dimensional texture map and extracting appearance features with real physical meaning, such as defect area and texture statistics; inputting these distortion-corrected appearance features and single-fruit weight data into a deep fusion network based on a cross-modal attention mechanism; and determining the final quality grade of the watermelon by mining deep correlations between modalities. This invention improves the objectivity of grading standards and the accuracy of predicting internal quality.

This invention discloses a method and system for multimodal video acquisition and tagging indexing in fire scenes. The method includes: S1: Deploying a multimodal camera array and sensor array, and synchronously acquiring video, smoke concentration, and temperature data through a hardware synchronization trigger; S2: Spatial registration of the video using a pre-calibrated homography matrix; S3: Adaptively adjusting weights based on smoke concentration to generate a fused video; S4: Automatically generating labels for fire stage, fuel type, and key moments based on temperature data and video features; S5: Storing the original video, fused video, temperature data, and labels in a three-level structure in a database, establishing a time index and a label index. This invention can achieve microsecond-level synchronous acquisition of multimodal videos such as visible light, near-infrared, and thermal infrared, while automatically identifying fire stage, fuel type, and key events, generating structured labels without manual intervention; providing a high-quality, multi-dimensional, and searchable experimental data foundation for fire mechanism analysis, firefighter case teaching, and fire identification.

This invention provides a method for virtual digital lofting and real-time calibration of installation pose of a guide rail, comprising: providing at least two positioning fixtures, each fixture having three collinear optical markers symmetrically arranged on both sides relative to the center marker; fixing the two positioning fixtures to the upper and lower ends of the guide rail respectively, so that the positioning fixtures are in close contact with the two working surfaces of the guide rail; acquiring the global coordinates of all optical markers in real time through a motion capture camera array, and independently calculating the six degrees of freedom pose deviation of the guide rail based on a coordinate comparison scheme corresponding to the layout of the positioning fixtures: calculating the horizontal translation deviation of the upper end of the guide rail; calculating the tilt angle deviation of the guide rail in the vertical plane; calculating the rotation angle deviation of the guide rail about its own length axis by using the coordinate difference of the two markers on both sides of the same positioning fixture on a single coordinate axis; and making targeted adjustments to the installation state of the guide rail according to the calculated pose deviations of each degree of freedom, thereby completing real-time calibration.

This invention discloses a dynamic obstacle avoidance and automatic landing optimization system for unmanned aerial vehicles (UAVs) in multiple scenarios and across the entire domain, relating to the fields of UAV defense and environmental perception technology. The method includes: controlling a scanning UAV equipped with a camera array to collect spatial and ground images, simultaneously acquiring attitude and positioning data; a processing center preprocessing and seamlessly stitching the images to generate a panoramic image of the entire environment; fusing multi-source monitoring data to form a complete dataset covering both indoor and outdoor environments; constructing a multi-index evaluation model to identify safe, landable areas through semantic segmentation and target detection; transmitting environmental data to a receiving device, guiding it to automatically aim and send appropriate landing commands. This invention achieves 360-degree, all-around environmental detection without blind spots, expands the coverage of landable areas, and improves the accuracy of safe area identification and the coordination between scanning and landing.

A system for inline inspection of a pipeline where the system includes: an inline vehicle to transport the system along the pipeline; a depth camera array (DCA) of multiple RGBD cameras located on an end of the vehicle, circular lights attached around the cameras to illuminate inside the pipeline, and a controller connected to the DCA.

This utility model relates to a novel Wood's lamp, comprising a handle, a connecting rod, a mounting box, a connecting plate, a lamp source assembly, and an external light-shielding assembly. The mounting base of the lamp source assembly has a conical outward-expanding lamp cavity and a ring-shaped camera array. The light-shielding cover of the external light-shielding assembly adopts a split magnetic suction structure, and its elastic layer is a waveform silicone integrated pressure sensor to achieve dynamic sealing and trigger the light source. The mounting box has a built-in AI processor and an anti-interference heat dissipation system. This utility model overcomes the limitations of darkroom environments, achieving accurate detection of skin lesions under sunlight through the synergy of physical light shielding and electronic light filtering, and is particularly suitable for imaging curved surfaces without blind spots.

A method for damage detection and safety assessment of fiber ropes in ultra-deep vertical shaft hoisting involves simultaneously acquiring terahertz image sequences of internal fiber rope damage and visual image sequences of surface damage using a multi-view camera array monitoring unit located on both sides of the U-shaped detection groove of the hoisting fiber rope, including a terahertz source transmitter, a terahertz imager, and a multi-view camera array at the sheave. Both types of detection data are transmitted to a host computer in real time. Next, the image processing and analysis unit in the host computer performs automatic target identification and preprocessing on the fiber rope detection data. Then, a spatiotemporal synchronous registration method based on SURF feature extraction and RANSAC algorithm optimization is used to obtain precise matching features and spatial mapping relationships of internal and external fiber rope damage. Finally, damage feature extraction and multimodal feature fusion are performed on the spatiotemporally registered multimodal detection data to achieve intelligent identification and precise location of fiber rope damage. Combined with damage quantification indicators, this enables safety assessment and graded early warning of fiber rope operation.

The application discloses a visual analysis-based intelligent detection method and system for piston surface defects of an automobile air conditioner compressor, and relates to the technical field of product quality detection.The method comprises the following steps: S1: multi-view image processing: at least three ring-shaped camera arrays are used to collect full-surface images of the upper end ball head area, the middle rod body area and the lower end conical surface area of the piston, and corresponding full-surface images of the piston are obtained; S2: intelligent defect recognition: the full-surface images of the piston are used as the input of a multi-scale feature fusion deep learning model, and corresponding recognized defects are obtained; and S3: defect mapping determination: according to corresponding camera coefficients in the ring-shaped camera arrays, the recognized defects are mapped to a three-dimensional digital model of the piston, and a corresponding defect detection report is obtained.The application realizes high-precision, high-efficiency and full-automatic detection of the piston surface defects of the automobile air conditioner compressor, and reduces the subjectivity and fatigue errors of manual detection.

The present application belongs to the field of artificial intelligence and rail transit safety detection technology, and specifically relates to a multi-view fusion subway car body damage intelligent discrimination system, aiming to solve the problems of low detection efficiency, high missed detection rate and difficult multi-source data fusion of subway car body damage detection. The system realizes omnidirectional scanning of the car body by arranging a multi-view visible light and infrared camera array; uses time-space synchronization and space alignment technology to complete multi-source image registration; uses a double-branch network to extract visible light details and thermal field anomaly features, and performs feature-level fusion through a cross-modal attention mechanism; combines time series evolution analysis and Dempster-Shafer evidence theory to realize decision-level fusion and improve discrimination robustness; the central diagnostic server carries out trend prediction and health assessment based on a knowledge graph, and supports automatic early warning and operation and maintenance decision-making. The system has online self-learning and equipment self-diagnosis capabilities, significantly improving detection accuracy and operation and maintenance intelligence level.

This invention relates to the field of fish monitoring technology, and discloses a fish monitoring method, device, electronic equipment, storage medium, and program product. The fish monitoring method includes: acquiring the ultrasonic encoded signal of the target fish when it enters a preset detection range; verifying the ultrasonic encoded signal; when the verification result is successful, controlling the image sonar device and optical camera array to start; locating the target fish using the image sonar device to obtain sonar image data; acquiring image data of the target fish using the optical camera array; associating the sonar image data and the image data to obtain a target association result; and monitoring the target fish based on the target association result. This invention improves the accuracy of fish monitoring by using ultrasonic detection of fish and monitoring the fish using a camera and sonar device when the fish are detected.

The application discloses an imaging system and method for microbial contamination of a cylindrical plant tissue culture bottle, and belongs to the field of plant culture. In view of the problem that the existing detection of the cylindrical tissue culture contamination is poor in precision and slow in efficiency, the application provides an imaging system for microbial contamination of a cylindrical plant tissue culture bottle, which comprises a camera array module for photographing a plurality of different height positions of the cylindrical plant tissue culture bottle; a light source matrix module for providing a plurality of groups of light sources to cooperate with the camera array module to image the cylindrical plant tissue culture bottle at different height positions; the camera array module corresponds to different groups of light sources at different height positions of the cylindrical plant tissue culture bottle; an imaging control module for controlling the camera array module and the light source matrix module to complete image acquisition of the cylindrical plant tissue culture bottle; and an image control module for image processing and transmission. The application improves the detection capability and precision of the microbial contamination in the cylindrical plant tissue culture bottle, guarantees the efficiency, and can realize industrial application.

This utility model relates to the field of mechanism gear technology and discloses an automated inspection device for mechanism gears, including a housing. The device uses a motor fixed to the inner wall of the housing. When the motor runs, it drives the gear to rotate via a connecting rod. The gear meshes with a gear ring, which in turn drives a transparent rotating disk to rotate. The transparent rotating disk slides along the outer wall of the inner groove via a rotating block, allowing the product to move on the disk. A support column supports a visual inspection camera array, which operates with a layout of two cameras (top and bottom) and three cameras (horizontal). The top camera vertically captures the top surface of the gear, the bottom camera captures the bottom surface of the gear through the transparent rotating disk, and the three horizontal cameras focus on the surface finish and inter-tooth gaps, respectively. Industrial image algorithms are used to extract edges and compare features from images at various angles for accurate identification, thereby accurately inspecting the product, improving inspection efficiency, and ensuring the stability of inspection quality.

A camera system integrated into the trocar. The camera system allows for a wide view of the internal surgical site and 3D mapping of fiducial markers during a laparoscopic procedure. Once inside the patient, the camera system is configured to deploy from a recessed position in the distal end of the trocar. In various aspects, the internal camera system is configured to keep the trocar port free for surgical instruments and provide surgical personnel with an expanded view of the surgical environment.

The present application relates to the technical field of image recognition and industrial vision detection, and discloses an electronic atomizer sensing signal data reading method based on image recognition, which comprises the following steps: collecting panoramic images through an industrial camera array and simultaneously locating LED indicator lights and tester screens by using a double-class YOLO detection network; estimating and compensating the interference of LED halos on screen areas based on a point spread function; unsupervisedly analyzing screen layouts through multi-scale Canny edge detection and Hough transformation; respectively performing OCR recognition and skeleton extraction on screen numerical reading areas and waveform areas; after adaptive brightness normalization and optical crosstalk compensation are performed on LED sub-images, extracting timing code matching sensing signals; and finally cross- verifying double-source data and outputting batch reading results.

The application discloses a hair perming device with a scalp health detection system and a detection method. Through an image processing system integrating a camera array and a processor, quantitative detection and objective analysis of key indicators of the scalp (such as hair grease, dandruff, redness, etc.) can be performed before, during and after hair perming, which completely changes the traditional subjective and rough judgment mode relying on naked eyes and experience and provides scientific data basis. Moreover, through real-time monitoring, the sub-health or risk state (such as inflammation, sensitivity, damage, etc.) of the scalp can be identified in time, and when high risk is detected, the system can automatically issue an alarm or intervention, thereby effectively preventing safety problems such as contact dermatitis, hair follicle damage and aggravated hair loss caused by improper hair perming operation.