14152 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.

Disclosed in the present invention are a danger test case generation method for a visual perception algorithm, and a related device. The method comprises: acquiring images captured by a visual sensor of a self-driving vehicle, cleaning and marking the collected images, and obtaining an observation data set according to no-reference image quality evaluation features; according to the observation data set and by means of performing fusion with domain knowledge, constructing a causal structure diagram that indicates the influence of environmental factors on perception performance; separating key environmental factors from the causal structure diagram, and quantitatively calculating the degree of influence of each environmental factor on visual perception performance; and on the basis of qualitative analysis of a causal relationship between a key environment variable and the visual perception performance, and quantitative estimation of a causal effect, proposing a challenge index, so as to generate, in batches, danger test cases for perception. The present invention has significant advantages in multiple aspects such as causal relationship mining, challenge index measurement, dangerous-scenario recognition and search space modeling, such that the performance of a visual algorithm for self-driving in a complex environment is evaluated and verified more accurately.

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 invention relates to the technical field of intelligent building management, in particular to a construction site comprehensive management system based on machine vision, which comprises an image capturing and partitioning module, a construction state analysis module, a component progress matching module, a progress deviation analysis and early warning module, a task dynamic allocation module and a construction node optimization module. According to the invention, through regionally extracting and numbering image data and combining a position coordinate subdivision technology, accurate partitioning and ordered data organization of a construction site are realized, the structural property and traceability of image data are guaranteed, real-time image analysis is carried out to compare the image data with a construction plan, the state of a component is identified, and progress deviation is revealed; a dynamic early warning mechanism is established, abnormal areas are marked, risks are prompted in advance, resource allocation is concentrated in key areas based on real-time progress and task priorities, task distribution and resource use priorities are optimized, reasonable and efficient allocation of resources is achieved, and therefore intelligence, reliability and safety of construction management are improved.

Disclosed herein are system, apparatus, device, method and / or computer program product embodiments, and / or combinations and sub-combinations thereof for blending multiple images of a financial instrument (e.g., check) into a single blended image to mitigate potential image errors. The method generates a confidence score for each of the plurality of images of the financial instrument, selects, based on the confidence score, a number of images of the financial instrument, ranks the number of images, arranging them from a highest to lowest confidence score, and assigns a weighting value, such as transparency, to each image of the selected number of images of the financial instrument, based on a respective ranking. The method builds a blended image by blending pixel content of common pixels, as modified by a respective weighting value, from the number of images and communicates the blended image to a remote deposit server.

Systems and methods disclosed herein include a mobile solution to enable users to perform financial transaction over a network using a mobile device. These techniques allow users to maintain a single personal account identifier or number (“PAN”) on the user's mobile device and to utilize it to access a plurality of linked financial accounts and sub-accounts. Any one of the accounts can be selected by a user on the mobile device to remotely deposit funds to that account based on an image of a financial payment instrument. The image can be obtained using image capture technology on the user's mobile device. Users can perform a financial transaction using the verified images over a network in order to conduct a remote financial transaction such as applying a deposit, a payment, or cash load to a designated account which is linked to the user's mobile account in real-time or near real-time.

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.

An unmanned aerial vehicle (UAV) that includes: a chassis; a plurality of arms that extend outwardly from the chassis; a plurality of propeller assemblies that are supported by the plurality of arms; a canopy that is connected to the chassis so as to provide an outer cover for the UAV that is configured to protect internal components thereof; a frame that is supported by the canopy such that the frame is isolated from the chassis; and a plurality of image capture assemblies that are supported by the frame such that the frame separates the plurality of image capture assemblies from the chassis and the canopy so as to inhibit relative movement between the plurality of image capture assemblies during operation of the UAV.

The invention discloses a human face image quality assessment method and system and a computer readable storage medium, and relates to the technical field of human face image quality assessment, and the method specifically comprises the following steps: uniformly dividing a human face image captured by a camera in real time into a plurality of regions through a face key point detection method under the condition that there is an artifact effect; acquiring artifact quality evaluation information of each region of the face image in real time, evaluating the quality influence degree of artifacts on each region, and dividing each region into a high influence region, a middle influence region and a low influence region according to an evaluation result; and according to the division result of each region of the face image, constructing a dynamic intervention mechanism, and respectively performing corresponding intervention measures on the high-influence region, the medium-influence region and the low-influence region. According to the method, the problem of human face image quality evaluation misjudgment caused by artifact interference in a dynamic light source environment is solved, and accurate evaluation and efficient dynamic optimization of the image quality are realized.

A checkout terminal is provided. The checkout terminal comprises a camera array, a display device, a weight scale, and a control circuit. The control circuit is configured to identify, based at least on images captured by the camera array, product identifiers associated with a plurality of different items placed in a placement area and on the weight scale, determine a combined weight of the plurality of different items based on product weight information stored in a product database, retrieve a weight measurement measured by the weight scale, detect for unaccounted items based on comparing the combined weight the plurality of different items and the weight measurement, and in the event that an unaccounted item is detected, display, via the display device, instructions to move one or more items to identify the unaccounted item.

This application relates to the field of photographing technologies, and discloses an image processing method and an electronic device, so as to dynamically adjust LUTs in a process of photographing or visual recording, and enrich display effects of photographing or visual recording. The electronic device obtains a first image, where the first image is an image captured by a camera of the electronic device, and the first image includes a first shot object; the electronic device determines a first scenario corresponding to the first image, where the first scenario is used to identify a scenario corresponding to the first shot object; the electronic device determines a first LUT based on the first scenario; and the electronic device processes the first image based on the first LUT to obtain a second image, and displays the second image, where a display effect of the second image corresponds to the first LUT.

Certain examples described herein relate to a mapping system. An example mapping system has a differentiable mapping engine to receive image data comprising a sequence of images captured using one or more camera devices of an object as it navigates an environment and a neural network scene representation comprising a neural network architecture trained to map input coordinate tensors indicating at least a point location in three-dimensional space to scene feature tensors having a dimensionality greater than the input tensors. The neural network scene representation is communicatively coupled to the differentiable mapping engine and the differentiable mapping engine is configured to use the neural network scene representation as a mapping of the environment during operation of the differentiable mapping engine.

A system, in particular an auto-commissioning system comprising an image capturing means, such as a camera, arranged to capture an image of an area, and a processing means configured to perform the steps of controlling the image capturing means so as to capture a sequence of images over time, processing said captured sequence of images over time to detect at least one scene element in said area, selecting at least one application from a list of applications, such as a traffic monitoring application or a parking monitoring application, based on a result of the processing and configuring the at least one application based on the captured sequence.

Systems, apparatuses, methods, and computer program products are disclosed for predicting an emotion in real-time based on facial gestures and limb gestures derived from captured images. An example method includes receiving a series of images captured in real-time. The example method further includes causing generation of a face segmentation and one or more limb segmentations using the series of images. The example method further extracting one or more face segmentations vectors and one or more limb segmentation vectors. The example method further includes causing generation of weighted vectors using the one or more face segmentation vectors and the one or more limb segmentation vectors for each of the one or more the limb segmentations. The example method includes calculating a probability distribution based on the one or more probabilities corresponding to one or more emotions. The example method finally includes determining a predicted emotion based on the probability distribution.

To simulate a 3D image of a subsurface below a surface, the system having a memory device for storing an instruction, a processor in communication with the memory device configured to execute the instruction, and a subsurface image capture module in communication with the processor, the subsurface image capture module having one or more wave generating device and one or more sensor affixed to a vehicle to capture a series of digital image datasets of the subsurface with a coordinate reference data, wherein the processor executes an instruction to generate a digital model of the series of digital image datasets of the subsurface while maintaining the coordinate reference data, wherein the processor executes an instruction to determine a depth map of the digital model, and wherein the processor executes an instruction to identify a key subject point in the digital model, where subsurface includes an internal biology, below ground, underwater.

The invention discloses an industrial visual detection system based on multi-modal fusion, which belongs to the technical field of industrial data acquisition, processing and processing, and comprises a multi-modal data acquisition and calibration module, a scene image capture module, a visual information synthesis module, an algorithm optimization and training module and a multi-modal image output module, the multiple modules are integrated into the industrial visual detection system for multi-modal data acquisition, processing and fusion, high-quality original data are provided for subsequent image analysis, images of industrial scenes can be automatically captured under different illumination conditions, an original image database containing various illumination and scene conditions is constructed, and the visual detection system has the advantages of being simple in structure, convenient to operate and high in practicability. The system can operate stably, high-precision analysis and processing of the image data set in the industrial scene are realized, the corresponding fusion image is generated, the industrial visual inspection report is generated based on the fusion image, and the adaptability and reliability of the industrial visual inspection system are improved.

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 invention provides a camera extrinsic parameter calibration method, an image stitching method and an apparatus thereof. The calibration method can include: acquiring a plurality of images captured by the camera based on a plurality of sets of extrinsic parameters to be calibrated, wherein each of the plurality of sets of extrinsic parameters to be calibrated include a horizontal rotation angle and a vertical rotation angle; obtaining at least one matched image pair based on feature point matching among the plurality of images, wherein each matched image pair includes matched feature point pairs with a quantity satisfying a threshold condition; and calibrating the plurality of sets of extrinsic parameters to be calibrated according to a first difference representation between coordinate representations of each matched feature point pair of each matched image pair in a reference coordinate system.

The invention discloses a casting product appearance defect detection method and system based on machine vision, and particularly relates to the technical field of casting product defect detection. According to the method, casting materials of a production line are divided into different categories, the casting materials with abnormal absorptivity are identified, terahertz wave scanning is carried out on the casting materials, scattering images are obtained, and the stability of scattering point density distribution is evaluated; scanning by using a terahertz time-domain spectrometer, analyzing an amplitude fluctuation state of a time-domain signal and evaluating a waveform distortion degree; after comprehensive analysis, the quality of images captured by the imaging system is evaluated, the images are divided into different grades, defect detection is directly carried out on high-quality images, the quality images are centered, the accuracy of the images is analyzed, and the transmitting power and the scanning speed of terahertz imaging equipment are dynamically adjusted, so that the imaging quality is improved, and the accuracy and the efficiency of detection are remarkably improved; and the quality and safety of casting products are ensured, and the product quality problem and potential equipment faults caused by untimely defect detection are effectively avoided.

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 a crop adaptability detection method based on an HSV color segmentation algorithm. The method comprises the steps that S1, two TOF cameras are used for shooting the same crop area; s2, through fusion of a solid-state laser radar and cameras, synchronously obtaining three-dimensional information and color information of crops, enabling a laser radar point cloud to have RGB color information, carrying out HSV color space conversion on an image captured by each TOF camera, and carrying out color segmentation by using a preset threshold value to obtain a region of interest of a crop region; s3, fusing the color information and the depth information acquired by the two TOF cameras based on a double-shooting depth perception technology; s4, generating an adaptability detection result according to the fused information; according to the crop adaptability detection method based on the HSV color segmentation algorithm, the identifiability of crops in the image is improved, false detection caused by external environment changes is reduced, and effective detection and tracking of crop rows in a complex environment are realized.

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.

Embodiments are presented herein for trailer sway detection and mitigation using a camera mirror system. In one embodiment, a vehicle controller is provided comprising: one or more processors; a non-transitory computer-readable medium; and program instructions stored on the non-transitory computer-readable medium. When executed by the one or more processors, the program instructions cause the one or more processors to: monitor images captured by at least one image capture device to detect sway of a trailer being towed by a tractor; and in response to detecting sway of the trailer, cause a braking system to apply a brake to attempt to reduce to the sway of the trailer.

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.

A data processing device includes a plurality of cameras arranged according to a predetermined configuration, where each camera is configured to capture successive images and to detect a current location of one or more elements in the captured images with respect to a coordinate system of the camera, a processor to generate a common camera coordinate system in dependence upon the respective coordinate systems of the plurality of cameras, the common camera coordinate system comprising a set of locations in a three-dimensional space included within the field of view of the plurality of cameras, and a detector to detect a current location of a given element with respect to the common camera coordinate system based on images captured by the plurality of cameras, wherein for each camera, the processor is configured, in response to a detection by the detector that the current location of the given element corresponds to a location in the set of locations of the common camera coordinate system, to generate first data for that location in the set of locations indicative of a mapping between the coordinate system for the camera and the common camera coordinate system, and wherein in response to a detection of a location in the set of locations for which the first data is indicative of the mapping for two or more cameras with respect to the common camera coordinate system, the processor is configured to generate second data for that location indicative of a mapping between the coordinate systems for the two or more cameras.

The invention discloses an intelligent reconstruction and forecasting system and method for a three-dimensional wave field in a real marine environment, and belongs to the technical field of marine engineering. Comprising an unmanned aerial vehicle image capture module, an image preprocessing module, a feature recognition and parameter extraction module, a low-contrast and high-noise image processing module, a wave crest and wave trough recognition module, a wave feature analysis module, a wave feature analysis and prediction module, an unmanned aerial vehicle position adjustment module and a wave simulation and evolution module. By integrating an advanced image processing technology and an artificial intelligence algorithm, the spatial wave surface resolution of free waves and high-order bound waves is improved, and an accurate three-dimensional wave field is synthesized through synchronous superposition. Multiple high-altitude unmanned aerial vehicles can be used for collecting wave surface images under various sea conditions in real time, wave feature recognition and parameter extraction are carried out, and three-dimensional reconstruction of near-field, middle-field and far-field wave surfaces in the ocean is effectively achieved based on a wave evolution physical control equation.

An object is to output data with which it is possible to generate a virtual viewpoint image of high image quality while suppressing the amount of data. The information processing apparatus according to the present disclosure obtains virtual viewpoint information for identifying a position of a virtual viewpoint and a line-of-sight direction from the virtual viewpoint, generates color information for an element configuring three-dimensional shape data for identifying a three-dimensional shape of an object based on the virtual viewpoint information and a plurality of images captured from a plurality of imaging devices, and outputs the three-dimensional shape data and the color information.

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 discloses a KR stirring vortex radius image recognition method, which comprises the following steps of S1, establishing an image data acquisition system, and acquiring image data; s2, preprocessing the image data according to the number of frames so as to enhance the image data; s3, carrying out threshold segmentation with correction on each frame of image data; s4, selecting an image recognition baseline position; s5, establishing a region window, and identifying a stirring radius; s6, establishing a search micro window in the area window, and determining the position of the stirring radius; and S7, carrying out filtering processing on the real-time identification data so as to smoothly process the discrete data and eliminate abnormal identification values. According to the method, the real-time vortex radius is recognized by adopting a threshold segmentation technology and combining a selective area window progressive search technology aiming at an image recognition parameter (vortex radius), and rapid calculation and image capture accuracy of vortex recognition are realized.