9984 results about "Image capture" patented technology

The invention provides an automatic obstacle avoidance point selection and obstacle avoidance method for a photovoltaic station polled by an unmanned aerial vehicle, and the method comprises the steps: carrying out the real-time analysis of the image definition through image processing for a polling image captured by the unmanned aerial vehicle carrying different sensors, carrying out the classification and recognition of an obstacle according to the high-low difference of the definition, and optimizing the detection process of the obstacle; under the condition of different obstacle recognition speeds, the flight speed and height of the unmanned aerial vehicle are dynamically adjusted to obtain higher patrol image definition and obstacle recognition efficiency; an obstacle is recognized from the inspection image, and a recognition result is used for updating an obstacle avoidance database in the flight of the unmanned aerial vehicle; according to the obstacle avoidance database updated in real time and the current position of the unmanned aerial vehicle, an optimal obstacle avoidance path is planned, and the optimal obstacle avoidance path is transmitted to the unmanned aerial vehicle in real time for execution; and when the optimal obstacle avoidance path is executed, the unmanned aerial vehicle system continuously monitors the change of the surrounding environment, and if a new obstacle or obstacle movement is detected, the obstacle avoidance path is adjusted in real time.

Locator systems are disclosed for locating buried utilities such as conduits, cables, pipes. or wires. The locator system may include image-capturing and position and orientation measuring devices such as magnetic compass, accelerometers, gyros, GPS, and DGPS. The system may associate images captured during the locate process with buried utility position data and the other sensor data. These data and images may be further associated with terrain images from satellites or aerial photography to provide a highly precision map and database of buried utility locations and visual images of the burial site. Information so obtained may be transferred to a hand-held personal communication device, such as a smart phone to show the location of buried utilities in combination with photo-images and / or terrain maps.

The present disclosure is related to systems and methods of dashcam installation for providing instructions on placing a dashcam for a person or dashcam installer. Aspects of the present disclosure are related to providing a digital assistant for installing the dashcam in an acceptable position, where the dashcam can capture images of objects with acceptable quality (e.g., as determined by a machine learning model). In some embodiments, the dashcam detects a driver and provides inferences related to the current dashcam position. The inferences can be based on analyzing images captured by the dashcam in the current position, where the analysis can utilize a machine learning model. The inferences can also provide one or more instructions to move and / or tilt the dashcam to the acceptable installation position.

The invention provides a working method of a blind guiding robot based on a laser radar and a camera, and belongs to the technical field of mobile service robots. Accurate space structure information is provided through three-dimensional point cloud data, dynamic traffic characteristics such as traffic lights and zebra crossings are captured through visual images, and comprehensiveness of environmental perception is achieved through complementation of the space structure information and the visual images; through combination of environment information and traffic characteristics, passable areas and barrier distribution in a map are dynamically adjusted, dynamic changes such as traffic light switching and pedestrian movement are adapted, and a navigation route can be updated in real time; the characteristics of traffic light states, zebra crossing and the like are fused into path planning, it is ensured that the robot complies with traffic rules, real-time position and speed constraint, dynamic adjustment of motion trails and efficient obstacle avoidance can be carried out on the robot, and the robot can make a decision and optimize a path autonomously according to human social rules.

The present invention relates to a system (101) and method (401) for performing vision inspection on at least one photovoltaic cell or module; said system (101) is capable to detect defects (102) in said photovoltaic cell or module (103) by detecting shadow representation on image captured by at least one detector (119) when said defect (102) obstructs transflected light in said photovoltaic cell or module (103); said light emitted from at least one first light source (115); wherein said system (101) further comprises of at least one second light source (118) to perform photoluminescence inspection on said photovoltaic cell or module (103).

The invention discloses an inspection robot navigation method, system and device based on Beidou and binocular vision fusion and a storage medium, and relates to the field of robot navigation and obstacle avoidance, and the method comprises the following steps: carrying out multi-modal data fusion processing based on an initial coordinate of an inspection robot and an image captured by a binocular vision system to obtain an environment sensing result; carrying out global planning and local optimization based on an environment perception result, and carrying out cooperation to generate a trajectory planning scheme; based on the environment sensing result and the trajectory planning scheme, intelligent navigation cooperative regulation and control are carried out, and an inspection robot motion control strategy is obtained; by improving the environmental perception accuracy, optimizing the path planning and performing intelligent navigation regulation and control, the navigation problem of the inspection robot in complex environments such as a transformer substation can be effectively solved, the inspection safety and efficiency are improved, and the method has remarkable practical application value.

The invention discloses a fruit appearance defect real-time online detection method and system, and relates to the technical field of image processing, and the system comprises an image capture module, a feature extraction and analysis module, a 3D reconstruction module, a dynamic segmentation module, a defect quantification and grading module, and a topology analysis and detection module. According to the real-time online detection method and system for the fruit appearance defects, the defects of a traditional method in the aspects of detection precision, classification fineness and environmental adaptability are overcome by combining a plurality of processes of multispectral image capture, hierarchical feature extraction, high-dimensional clustering analysis, 3D modeling, defect quantitative evaluation and the like. The system can accurately identify various defect types on the surface of the fruit in real time in a complex detection environment and quantify the severity of the defect types. Compared with the prior art, the system has the advantages that the accuracy, the stability and the real-time performance of defect detection are remarkably improved, an intelligent solution is provided for automatic sorting and quality control of fruits, and meanwhile, the labor cost is reduced.

The invention provides a road surface defect detection method and system based on multi-sensor fusion, and the method comprises the steps: 1, capturing a road surface image through an RGB camera, and obtaining the three-dimensional point cloud data of a road surface through LiDAR; 2, performing feature extraction on the road surface image captured by the RGB camera by using a YOLOv5 network; step 3, processing the road surface three-dimensional point cloud data acquired by the LiDAR by using a Point Net + + network; step 4, carrying out deep fusion on the image features extracted by the YOLOv5 and the point cloud features extracted by the Point Net + +; and 5, detecting and classifying the road surface defects by adopting a quantitative and qualitative combined method. According to the method, an RGB camera and LiDAR (light detection and distance measurement) are adopted, a YOLOv5 network is combined with PointNet + +, high-precision and real-time detection and classification of road surface defects are achieved, and the defects of a traditional method are overcome.

Systems and techniques are provided for calibrating cameras in a real space for tracking puts and takes of items by subjects. The method includes first processing one or more selected images captured by an extrinsic calibration tool to extract from the images, a three-dimensional (3D) point cloud of points corresponding to displays or structures that remain substantially immobile in the real space, and a second processing of a second set of images captured by a camera installation in the real space to match points in the second set of images to the point cloud. Differences in position of matching points can be used to determine transformation information therebetween, which can be used to calibrate the installed cameras.

The invention provides a multi-scale polarization data fusion method based on a 4K polarization imaging detector, and relates to the technical field of image processing, and the method comprises the steps: carrying out the adaptive edge detection of four original polarization images, generating a comprehensive edge image, and carrying out the definition scoring; performing color calibration on each original polarization image based on the ambient light intensity and the color temperature, and outputting a polarization image after color calibration and a color deviation score; combining definition scores, color deviation scores and global brightness information entropies of the four polarization images after color calibration to construct a multi-objective optimization function, and solving the multi-objective optimization function in a multi-exposure parameter space to obtain an optimal exposure parameter combination; applying the optimal exposure parameter combination to image capture of the next period, and calculating global quality reward values of four newly collected polarization images; when the global quality reward value meets a preset condition, wavelet decomposition and frequency division multi-scale fusion are carried out on the polarization images after color correction, a fused image is generated, and the quality of the polarization images is effectively improved.

An electronic device is disclosed. The electronic device comprises an image acquisition unit configured to acquire medical images captured at a plurality of positions, and a processor configured to generate tree structure data of three-dimensional candidate points corresponding to points along center lines of blood vessel regions of a reference image and a sub-image of the medical images, determine a three-dimensional path based on the tree structure data, determine a three-dimensional diameter for each of the points on the three-dimensional path, and reconstruct the three-dimensional shape of the blood vessels corresponding to the three-dimensional path based on the determined three-dimensional diameter.

An apparatus for synthetizing medical images, wherein the apparatus includes a process and a memory containing instructions configuring the processor to receive an organ model related to a patient's organ, identify a region of interest within the organ model, wherein identifying the region of interest includes locating at least a point of view on the organ model and determining a view angle corresponding to the at least a point of view, wherein the at least a point of view and the corresponding view angle define at least one field of view that include at least a portion of the organ model, and generate at least a medical image as a function of the region of interest using an image generator, wherein the at least a medical image captures an anatomical structure of the at least a portion of the organ model.

A method for recovering a 3D mesh of N humans in a 3D scene comprises: encoding a 2D image from an image capturing device to extract embedded features for each of a plurality of regions; detecting N humans in N respective regions among the plurality of regions; processing the embedded features in the N respective regions and the embedded features for each of the plurality of regions to predict body model and depth parameters using a decoder comprising a cross-attention module; providing the predicted body model parameters to a 3D parametric model for generating 3D meshes; and placing the generated 3D meshes at respective 3D spatial locations based on the predicted depth parameters.

The invention belongs to the field of convolutional neural networks, and particularly relates to a coal seam hole wall crack capturing method based on a YOLO algorithm. According to the method, a large number of high-precision coal seam hole wall crack pictures are manually collected, data are preprocessed, feature information is extracted and then put into a model for repeated training, and a loss function is continuously optimized through back propagation, so that the model achieves the effect of accurately recognizing the coal seam hole wall cracks; and finally applying the trained model to an actual coal seam hole wall image, and capturing a coal seam hole wall crack. According to the method, the high-precision automatic identification function of the hole wall cracks of the coal seam is realized, the manual workload is greatly reduced, meanwhile, a guarantee is provided for the personnel safety of a coal mine, the coal mining efficiency is improved, and a scheme is provided for underground route arrangement of the coal mine.

The invention provides a text-to-dynamic three-dimensional scene generation method and device. The method comprises the following steps: acquiring a first natural language description input by a user and a plurality of scene images shot at different angles; generating a static three-dimensional scene according to the first natural language description and the plurality of scene images; a second natural language description input by the user to the large language model is obtained, the second natural language description comprises relative scale information and constraint information of the multiple objects, and the relative scale information is used for describing actual physical sizes of the multiple objects in the static three-dimensional scene; the constraint information is used for describing physical conflicts existing in the moving process of the multiple objects; and according to the second natural language description and the static three-dimensional scene, generating reasoning motion tracks and reasoning sizes of the plurality of objects in the static three-dimensional scene so as to obtain a dynamic three-dimensional scene. Through the scheme, the authenticity and richness of the automatic driving simulation test are improved.

The invention discloses a target tracking method fusing visual perception and motion control. The method comprises the following steps: improving a YOLOv8 model and pre-training the improved YOLOv8 model; s2, preprocessing an image acquired by a camera, inputting the preprocessed image into the YOLOv8 model trained in the step S1, and outputting a target bounding box and a target center pixel coordinate; target center pixel coordinates are transmitted to a development board of a pre-burning algorithm program through a serial port, the development board is designed according to a stepping motor mathematical model, sine acceleration and deceleration serve as the basis, PID control, sliding mode control and fuzzy control algorithms are fused, and code burning is generated after in-loop simulation optimization; and the development board drives a stepping motor to adjust the posture of the holder according to the target center pixel coordinate control instruction, so that the target stops moving after being kept in the view center. The problems that a traditional YOLOv8 model is large in target recognition error under the complex background, PID control is prone to oscillation under the nonlinear working condition, buffeting exists in sliding mode control, and response lags when fuzzy control is independently used are solved.

The present invention proposes a three-dimensional (3D) model reconstruction and rendering device, which includes a data collection module for obtaining required data from two-dimensional images captured by different photographic equipment, a model training module configured to obtain data from the data collection module to train the 3D modeling model and learn the ability to reconstruct and render 3D models and scenes, a 3D model and scene rendering module utilizing the 3D modeling model completed with training to convert the collected data into three-dimensional models and scenes, and a rendering and 3D effect module being used to process the generated three-dimensional models and scenes through the three-dimensional modeling and rendering software for further applications.

An imaging device includes an imaging element unit that is exposed to incident light and that outputs a captured image signal, a notification unit, and a control unit that performs control in such a way as to cause the notification unit to perform notification corresponding to still image capture exposure, which is performed by the imaging element unit to generate a still image in response to a still image capture instruction, in a period different from an exposure period of the still image capture exposure.

Provide is a display terminal having a small display space, in which high operability is realized while convenience is maintained. A display terminal including a photographing device comprises: an image analysis unit configured to analyze an image captured by the photographing device, use region information that is information of a region on the image which corresponds to a real object existing in the external field, and refer to an icon DB so as to specify an icon related to the real object; and an app start unit configured to obtain an application associated with the specified icon from an app DB and start the application.

The invention discloses an optical lens, an image capturing module and a terminal device, the optical lens comprises seven lenses with refractive power, the first lens has negative refractive power, the object side surface is a convex surface, and the image side surface is a concave surface; the second lens element with negative refractive power has a convex object-side surface and a concave image-side surface. The third lens element with refractive power has a concave object-side surface and a convex image-side surface, respectively. The fourth lens element with positive refractive power has a convex object-side surface. The fifth lens element with positive refractive power has a convex object-side surface and a convex image-side surface. The sixth lens element with negative refractive power has a concave object-side surface and a convex image-side surface, and the seventh lens element with positive refractive power has a convex object-side surface. The optical lens satisfies the following relational expression: 190default; a FOVlt; 210deg and 1.65 lt are included in the formula I; iMGH / Flt; 1.8). According to the optical lens, the image capturing module and the terminal equipment, the miniaturization design of the optical lens can be met, meanwhile, the large field angle can be achieved, and meanwhile the imaging quality can be improved.

The technical solutions described herein are systems and methods for multi-mode image capture device operation. The system can obtain, from a first image capture device in accordance with a first mode, a first set of images corresponding to a first range of angles about an axis. The system can obtain, from a second image capture device in accordance with the first mode, a second set of images corresponding to a second range of angles about the axis. The system can cause, responsive to an interruption of the first mode, the second image capture device to obtain a third set of images corresponding to the first range of angles about the axis in accordance with a second mode.

Embodiments of this disclosure can provide a system and method for training a perception model to perform an autonomous driving task. During operation, the system can obtain labeled training data comprising images captured by multiple cameras mounted at different locations on a vehicle, and the perception model can generate, in parallel, a prediction output associated with the task and a confidence score based on the labeled training data. The confidence score can indicate a level of uncertainty associated with the prediction output. The system can generate an uncertainty-weighted prediction based on ground truth indicated by the labeled training data, the prediction output, and the confidence score; compute a loss function based on the uncertainty-weighted prediction; and update the perception model based on the loss function.

An apparatus comprises an interface and a processor. The interface may be configured to receive pixel data representing a first field of view of a camera and four-dimensional (4D) point cloud data representing a second field of view of a 4D imaging radar sensor. The first field of view of the camera and the second field of view of the 4D imaging radar sensor generally overlap. The processor may be configured to process the pixel data and the 4D point cloud data arranged as video frames and perform an extrinsic parameter calibration for the 4D imaging radar sensor and the camera based on adaptive projection error. The extrinsic parameter calibration may comprise applying a pose calibration process to the video frames. The pose calibration process may use (i) a respective translate vector and a respective rotation matrix for each of the 4D imaging radar sensor and the camera and (ii) a radar corner reflector to obtain configuration parameters for the first field of view of the camera and the second field of view of the 4D imaging radar sensor. The pose calibration process generally comprises capturing data for a plurality of positions of the radar corner reflector between a near-distance value and a long-distance value, and modifying a scale of a projection error of the radar corner reflector based on a size of the radar corner reflector in an image captured by the camera.

The invention discloses a golf motion simulation method and system based on digital twinning, and the method comprises the steps: obtaining an original data set containing a timestamp and a space coordinate from the cooperative motion of a plurality of parts and equipment of an athlete body through a sensor network technology in combination with a high-speed image capture device, and obtaining a preliminary multi-source motion information record; aiming at the initial multi-source motion information record, correcting time synchronization deviation and space matching error by adopting a data preprocessing module, and determining a corrected unified data framework by comparing timestamps and coordinate mapping relationships of data sources; according to the corrected unified data framework, a feature extraction algorithm is used for separating and marking the action analysis details and key parameters at the ball hitting moment, and a feature vector set containing the body posture and the equipment state is obtained. According to the invention, a highly vivid virtual environment support is provided for exercise training and match analysis, and the simulation precision and application value of a virtual exercise scene are effectively improved.

The invention discloses a high-precision particle image velocity measurement method, and relates to the technical field of particle image velocity measurement, and the method specifically comprises the steps: 1, building a high-precision particle image measurement experiment platform, capturing continuous particle images through a laser-camera system with a synchronous time sequence, achieving the precise synchronization of laser pulses and camera exposure through an FPGA synchronous controller, and carrying out the measurement of the continuous particle images; the method comprises the following steps of: 1, acquiring a displacement image captured by a high-speed camera, and verifying synchronization precision, 2, processing the displacement image captured by the high-speed camera by using a technology combining a cross-correlation method and an optical flow method, and 3, introducing singular value decomposition in a PIV data processing process, decomposing flow field data, and separating main signals and noise. The sub-pixel-level precision of particle displacement measurement is remarkably improved, the signal-to-noise ratio of data is enhanced, and real-time error correction is achieved.

This disclosure provides systems, methods, and devices for image capture that support image processing. In a first aspect, a method of image processing includes receiving first image data from a first image sensor; receiving second image data from a second image sensor of a second camera, wherein at least one of the first image data or the second image data is received through a variable aperture (VA) having an adjusted aperture setting applied by the first camera or the second camera; and / or determining a first output frame based on the first image data and the second image data by adjusting the second image data to match a characteristic of the first image data. Other aspects and features are also claimed and described.

An imaging system improves image quality, such as during a videoconference, by adjusting one or more captured images based on a model of a scene, a conference participant's face or a combination thereof. The images are adjusted in response to identification of relatively poor ambient conditions for image capture. The imaging system, such as a videoconference system, is thus able to display relatively high-quality images even in relatively poor conditions for image capture.

Apparatus for identification of abnormal biomedical features within images of biomedical data and methods used therein are described. The apparatus includes an image capture device, a processor connected to the image capture device, a memory connected to the processor, and a display device connected to the processor. The image capture device is configured to capture an image of biomedical data. The memory contains instructions configuring the processor to receive the image, extract a plurality of biomedical features from the biomedical data, receive repository data from a medical repository as a function of the plurality of biomedical features, generate at least a distance metric as a function of the plurality of biomedical features and the repository data, and highlight at least a biomedical feature within the image as a function of the at least a distance metric.

A video conferencing method comprising a first and a second video conferencing device. In each video conferencing device, video images of a user are captured, transmitted to the other, remote video conferencing device, and displayed there by a display device. The invention further relates to a video conferencing system comprising a first video conferencing device having a first display device and a first image capture device, and comprising a second video conferencing device having a second display device and a second image capture device.