1087 results about "Onboard camera" patented technology

The invention discloses a traffic operation and maintenance fault intelligent scheduling method and system based on an AI large model, and belongs to the technical field of traffic control. The method comprises the following steps: collecting a vehicle driving track GPS coordinate set, a traffic flow density matrix, a vehicle-mounted camera monitoring image frame sequence and a fault vehicle owner speed anomaly detection result in real time; constructing a traffic operation state analysis model, and outputting real-time traffic operation state characteristics; generating a traffic fault probability distribution curved surface in a future time window; generating a comprehensive fault positioning confidence coefficient matrix; and planning an optimal maintenance resource path according to the pheromone updating rule, and updating the optimal maintenance resource path to the visual scheduling platform in real time. According to the method, space-time diagram convolutional network dynamic modeling is constructed according to multi-source data, so that the limitation of a space blind area of a single data source is broken through, the fault positioning speed is improved, and the problems of incomplete coverage and low positioning speed in the prior art are solved.

The invention discloses an automobile data recorder fatigue driving detection and reminding method based on multi-modal data fusion, and the method comprises the following steps: S1, collecting and preprocessing a face image through a vehicle-mounted camera, and carrying out the face detection and region positioning; s2, dynamically adjusting the size and the position of an image block by adopting a dynamic image blocking technology; s3, performing facial image feature extraction by using a visual converter; s4, acquiring vehicle multi-modal data and fusing the vehicle multi-modal data with the facial features; s5, optimizing a visual converter network structure and training hyper-parameters through a wolf pack optimization algorithm; s6, performing fatigue state analysis based on the optimized visual converter; and S7, when the fatigue state is detected, reminding the driver to have a rest through sound-light alarm. The fatigue driving detection and reminding method of the automobile data recorder is high in precision and high in real-time performance through a deep learning algorithm of multi-modal data fusion and optimization, and the recognition accuracy of fatigue driving and the robustness of the system are effectively improved.

The invention relates to the technical field of unmanned aerial vehicle navigation, and discloses an unmanned aerial vehicle navigation method and system based on computer vision, and the unmanned aerial vehicle navigation method based on computer vision comprises the following steps: collecting a current visual field image of an airborne camera of an unmanned aerial vehicle, and carrying out adaptive image enhancement; performing scene semantic understanding; semantic perception feature extraction is carried out; feature matching and outer point elimination are carried out; floor identification is carried out, and multi-sensor fusion positioning is carried out; plane segmentation, structural constraint extraction and map normalization are carried out; performing visual navigation evaluation, judging a navigation mode according to an evaluation result, and generating an exploration control instruction quantity based on the navigation mode; generating a cross-floor path sequence, optimizing a track in real time, and performing control fusion in combination with a navigation mode identifier and an exploration control vector; according to the method, the navigation problem of the unmanned aerial vehicle in complex scenes such as smoke interference, multi-story buildings and illumination dramatic change in a GPS denial environment is solved, and high-precision autonomous navigation is realized.

The invention provides a driving behavior intelligent identification method and system based on video analysis, and the method comprises the steps: obtaining a driver face video stream and a road environment video stream collected by a vehicle-mounted camera, and reading the driving information recorded by a whole vehicle communication network; recognizing an eyelid closing state, a sight line direction and a head posture in the driver face video stream based on a posture recognition model, and performing fatigue distraction analysis to obtain driver state information; performing motion trail analysis on the road environment video stream and the driving information, and performing driving risk assessment in combination with the driver state information to obtain driving assessment information; and performing early warning construction according to the driving evaluation information, generating early warning prompt information, and synchronously writing the early warning prompt information, the driving evaluation information and the driver state information into a safety data protection memory. The fatigue and distraction states of the driver can be recognized more accurately, and the accuracy of state judgment is improved.

The invention relates to the technical field of intelligent driving, and discloses a defogging embedded system and method for an intelligent driving vehicle-mounted camera, and the method comprises the steps: obtaining original image data collected by the vehicle-mounted camera, and analyzing the brightness distribution, color shift and texture features in an image; based on the image degradation feature information, performing preliminary enhancement processing on the image by adopting an edge guided filtering and brightness adaptive mapping algorithm to generate an initial enhanced image; carrying out fog distribution estimation on the initial enhanced image, carrying out detail restoration and color compensation in combination with a lightweight image reconstruction strategy, and dynamically improving the image quality through an iterative optimization mode; performing definition evaluation on the optimized image, and measuring the fuzzy degree change trend and the structural similarity; and in combination with the finally output clear image, performing target identification and feature extraction operation, and performing accuracy evaluation on an identification result. The method has the advantage of improving the definition of the intelligent driving image.

The invention provides an ai-driven mud head vehicle illegal behavior cooperative monitoring method and system, and the method comprises the steps: collecting the three-dimensional acceleration and three-dimensional angular velocity data of a mud head vehicle through a vehicle-mounted inertial sensor, and constructing an inertial behavior sequence; establishing an individualized behavior model based on historical normal behavior data, identifying an abnormal behavior period deviating from a normal state, and generating an abnormal score; when the abnormal behavior exists, a vehicle-mounted camera is triggered to collect an environment image, and the legality of the scene where the mud-head vehicle is located is judged through a visual semantic recognition model; and fusing the abnormal score and the scene legality mark, and generating a final violation judgment result of the violation behavior through a joint judgment model. And according to the violation judgment result, triggering a multi-stage linkage response mechanism, including vehicle-mounted real-time feedback, regional monitoring equipment linkage and violation data uploading and evidence storage.

A vehicular camera includes a lens unit, a circuit board, an imaging element, a housing supporting the lens unit and accommodating the circuit board and the imaging element, a shield made of metal that is disposed in an internal space of the housing to surround the circuit board, and a resin member that contains a magnetic material, has a predetermined thermal conductivity, and is disposed between the circuit board and a first bottom surface portion of the shield in a manner of extending over an entire circumference of the hole including a central portion of a second shape of the first bottom surface portion of the shield. The resin member is in contact with a second surface of the circuit board, first to fourth side surface portions of the shield, and first bottom surface portion of the shield.

A vehicular camera monitoring system includes an electronic control unit (ECU) at a vehicle and a support arm movably disposed at a side portion of the vehicle, with the support arm having a base end attached at the side portion of the vehicle and a distal end opposite the base end. A camera is disposed at the distal end of the support arm. The support arm is movable between a stowed position and an extended position. A cover element covers an aperture at the side portion at least when the support arm is in the extended position. The camera, when the support arm is in the extended position, captures image data and provides captured image data to the ECU, which processes the provided image data for (i) display of video images derived from provided image data and / or (ii) detection of an object in the field of view of the camera.

The invention discloses a multi-degraded image restoration method based on semantic guidance. According to the method, for degraded images captured by a vehicle-mounted camera under severe weather conditions, potential features of the images are extracted by adopting a trunk network based on Transform, multi-modal semantic information is extracted in combination with a CLIP visual language model, and semantic guidance is provided for different degradation types through a dynamic text prompt generation mechanism. A self-adaptive feature fusion module is designed, channel attention and space attention mechanisms are combined to realize effective integration of multi-modal features, and a degradation feature extraction and fusion module is introduced to enhance the generalization ability of the model. According to the semantic guidance multi-type image recovery network SGIRN provided by the invention, the global modeling capability of the Transform and the cross-modal representation capability of the CLIP visual language model are combined, so that high-quality recovery of various weather degradation types is realized.

Various systems and methods are presented regarding utilizing technology onboard a vehicle to mitigate the effects of communication signals being deleteriously affected / lost when operational surroundings cause occlusion / loss of receipt of positioning / location signals at the vehicle. The vehicle can be operating non-autonomously, partially autonomously, or autonomously. To supplement the lost / occluded signals position information of other systems proximate to the vehicle can be obtained / utilized. The other systems can include another vehicle, a mobile device, an internet, and suchlike. Also, onboard devices can be utilized to determine the location, such as an onboard camera system providing information regarding street signs, building facades, and suchlike.

The invention discloses a multi-source fusion real-time traffic perception and emergency early warning system and method based on vehicle and road cloud cooperation, and relates to the technical field of traffic management. The vehicle end system comprises an information acquisition and transmission module, a local decision module, a data receiving module, an emergency response module and a data feedback module, and the information acquisition and transmission module acquires vehicle peripheral information through a vehicle-mounted radar and a vehicle-mounted camera. According to the invention, a vehicle end collects local information such as obstacles around a vehicle and dynamic states of adjacent vehicles through a vehicle-mounted radar and a camera, a road end collects regional information such as road section traffic flow density, road damage and traffic facility states through a roadside camera and a sensor, and a cloud end integrates data at the two ends and carries out time-space synchronization through a multi-source fusion technology. The defect of a single vehicle end or road end sensing blind area is overcome, and complete sensing of the traffic state of the whole road network is achieved.

A vehicular camera includes a lens unit, a circuit board, an imaging element, a plurality of electronic components disposed on first and second surfaces of the circuit board, a circuit board connector connection portion disposed on the second surface of the circuit board, a housing including a second tubular portion that accommodates at least the circuit board and the imaging element, a metallic first planar member covering at least a part of the plurality of electronic components disposed on the second surface of the circuit board and electrically connected to the circuit of the circuit board, a connector including at least one terminal that extends across an inside and an outside of the housing, and a metallic tubular member that surrounds at least a part of the at least one terminal of the connector around the direction along the optical axis and has a tubular shape.

The present disclosure provides a method and apparatus for generating an aerial view of a vehicle, a storage medium, an electronic device, and a vehicle. The method comprises: obtaining a road scenario image set of a plurality of directions acquired by a vehicle-mounted camera of a target vehicle; preprocessing the road scenario image set into a target image set of a target size, and obtaining camera parameters of the vehicle-mounted camera; using a convolutional network to extract multi-scale image features of the target image set, and using the central point of the target vehicle as an original point to create a three-dimensional coordinate grid; and using the multi-scale image features, the camera parameters, and the three-dimensional coordinate grid to generate an environment aerial view of the target vehicle.

The invention relates to the technical field of electric connection, in particular to a vehicle-mounted camera connector assembly which comprises a shell connector and a plate end connector, the shell connector comprises a shell, a power connection assembly and a fixing plug, the power connection assembly is arranged in the shell, and the fixing plug is used for fixing the power connection assembly in the shell. The power connection assembly is provided with a first power connection terminal, a first plugging end and a second plugging end. The two ends of the first power connection terminal extend to the first plugging end and the second plugging end respectively. The board end connector comprises a base, a floating seat, a fixing piece, a floating connecting piece and a second power connection terminal, the base and the floating seat are both independently formed by insulating materials, and the fixing piece and the floating connecting piece are both independently formed by conductive metal pieces. Stable and reliable electric connection, good floating compensation, buffer protection and efficient and convenient assembly and maintenance are achieved, and the high-quality signal transmission requirement of the vehicle-mounted camera in a complex vehicle environment can be met.

The invention relates to the field of automobile electronic testing technology and equipment, and discloses a vehicle-mounted camera imaging quality testing method and device suitable for a rain and fog scene, and the method comprises the steps: installing a to-be-tested camera module in a rain and fog environment cabin, setting the spectrum and illumination of a top natural illumination simulation system, and simulating the illumination at different time periods; selecting a test target plate in the darkroom; starting an automatic centering module to align the optical axis with the standard plate reference; rain and fog parameters are set through the environment control host, the rain and fog supply system is started to simulate different levels of rain and fog environments, and the raindrop particle size, concentration, dripping speed, fog visibility and fogdrop particle size are dynamically regulated and controlled; shooting a target plate graph card, extracting characteristic parameters by an image analysis module, performing quantitative analysis, and generating an evaluation report, so as to solve the technical problem of singleness of rain and fog scene environment simulation in the prior art.

The invention belongs to the technical field of image processing, and particularly discloses a vehicle-mounted camera image denoising and enhancing method and system, an image is decomposed into sub-band images with different frequencies through multi-scale decomposition, so that noise and details are processed on different scales, aiming at the characteristics of different sub-bands, a self-adaptive algorithm is adopted to estimate noise intensity, and the noise intensity is improved. According to the method, a high-frequency sub-band image is estimated, adaptive denoising processing is carried out according to the estimated noise intensity, the denoising effect is ensured, meanwhile, blurring of edges and textures is reduced, the processing quality is improved, detail enhancement operation is carried out on the denoised high-frequency sub-band image, a deep learning model structure and parameters are optimized in the training process, and the robustness of the high-frequency sub-band image is improved. The method can effectively improve the image quality under limited computing resources, the design of the deep learning model reduces the calculation amount, the powerful feature learning capability of the deep learning model can capture the image features which are difficult to process by a traditional method, and the denoising and enhancement effects are further improved.

The invention provides a low obstacle detection method and device based on multi-sensor fusion and a medium, and relates to the technical field of automatic driving. The method comprises the following steps: acquiring a road image acquired by a vehicle-mounted camera, and performing low obstacle detection on the road image by using a preset target detection model to obtain identification information and a first position of a first low obstacle; acquiring radar data acquired by the millimeter wave radar, and determining a second position of a second low obstacle according to the radar data; performing target fusion on the identification information and the first position of the first low obstacle and the second position of the second low obstacle to obtain candidate obstacle information; and obtaining target point cloud data collected by the laser radar, and determining the target position and the target size of the low obstacle according to the candidate obstacle information and the target point cloud data. According to the method, the detection precision of the position and the size of the low obstacle is improved, the detection accuracy is improved, and false detection is avoided.

The invention relates to a road crack detection method and system based on a zero-sample large language model, and relates to the technical field of computer vision and artificial intelligence. The method comprises the steps that a road surface image is collected through an unmanned aerial vehicle or a vehicle-mounted camera, after denoising and contrast adjustment preprocessing, visual features are extracted through a multi-modal model and converted into text description, and an image-text embedding vector is generated; semantic reasoning is performed on the embedded vector based on a large language model, zero sample classification is realized through similarity matching of predefined text tags, and crack types and severity are identified; and generating a restoration suggestion in combination with the road environment and the traffic load data, and outputting a detection result and a user feedback optimization model through a visual interface. The method can realize high-precision crack detection without labeling data, has the advantages of strong generalization, multi-modal fusion, intelligent decision support and the like, and can be widely applied to health monitoring and maintenance of infrastructures such as roads, bridges and the like.

The invention relates to an automobile windshield shelter removing method and system and an automobile, and belongs to the technical field of automobile active safety. The method comprises the steps that the surface of the windshield is monitored through a vehicle-mounted camera; when a shielding object is identified, calculating a view shielding coefficient based on the area, the position, the light transmittance and the type of the shielding object, and determining an initial influence level according to the view shielding coefficient; corresponding cleaning strategies are executed according to the influence levels, windscreen wiper cleaning is started at the low level, pneumatic suction generated by vehicle intersection is used for cleaning at the middle level, and negative-pressure airflow cleaning is induced through dynamic opening of a skylight at the high level; if the shielding is not removed, the influence level is increased step by step, and circulation execution is carried out until the shielding is removed or automatic parking is triggered. According to the method, grading, closed-loop and non-contact intelligent removal of different types of sheltering objects is achieved, and invalid or even harmful operation of a traditional windscreen wiper in a dry sheltering scene is effectively avoided.

The invention relates to the technical field of image processing, and provides an excavator operation safety monitoring method based on visual assistance and a laser radar, which comprises the following steps: acquiring continuous frames of monitoring images in the excavator operation process through a vehicle-mounted camera, and acquiring three-dimensional point cloud data at a plurality of moments through the laser radar; obtaining a target movement degree of each region, screening to obtain a plurality of moving targets and obtaining a movement sequence of the moving targets; obtaining the target influence degree of each moving target at each moment; the comprehensive influence degree of the moving target is obtained; screening an interference target based on the comprehensive influence degree, and obtaining an interference sequence of the interference target in combination with the moving sequence corresponding to each vehicle-mounted camera; and according to the interference target and the interference sequence thereof, collision early warning is carried out through an audible and visual alarm, and safety monitoring of excavator operation is achieved. The invention aims to solve the problem that the blind area and collision detection accuracy of a fusion result can be interfered by respective misrecognition problems of computer vision and laser radar.

An optical axis position adjuster according to the present disclosure includes a target board, a leg portion that supports the target board, and an installation auxiliary jig that connects the leg portion and the vehicle. The leg portions can be installed horizontally with respect to the ground. The installation auxiliary jig is connected to a connecting portion provided in the leg portion and is connected to an emblem provided in the vehicle. The connecting portion is disposed at the center of the leg portion, and the emblem is disposed at the center of the vehicle in the vehicle width direction. Therefore, it is possible to connect the vehicle and the leg portions such that the center of the target board and the center of the vehicle in the vehicle width direction coincide with each other in a plan view.

The invention discloses a vehicle-mounted camera self-cleaning method and system and a vehicle, and relates to the technical field of vehicle-mounted camera self-cleaning. The method comprises the following steps: starting a vehicle and executing self-cleaning once; monitoring the environment and the dirty condition of the vehicle-mounted camera; transmitting a cleaning signal; the cleaning signal is recognized, and corresponding cleaning steps are executed; stopping the vehicle and ending self-cleaning; the system comprises a plurality of cameras, each camera is provided with a plurality of air nozzles, the air nozzles are communicated with an electromagnetic valve through pipelines, and the electromagnetic valve is communicated with a high-pressure air source through a pipeline; the electromagnetic valve is electrically connected with a controller, and the controller is further electrically connected with a display screen, a raindrop sensor, a manual switch and the camera. The vehicle comprises the vehicle-mounted camera self-cleaning system. The device does not directly contact the surface of the camera, lens abrasion is avoided, different cleaning strategies can be executed according to rainfall, and the problems that in the prior art, a lens is prone to abrasion, and the rainwater cleaning capacity is poor can be effectively solved.

The embodiment of the invention provides a vehicle damage event recording method, a data query method, a vehicle and a storage medium, and relates to the technical field of vehicles and data processing. The method comprises the steps that perception data of a vehicle are obtained based on a vehicle-mounted sensor, visual data of the vehicle are obtained based on a vehicle-mounted camera, and the visual data are used for reflecting the environment state and the damage state of the vehicle; detecting the vehicle based on the perception data and the visual data to obtain a detection result; in response to the detection result indicating that the vehicle has the damage event, performing block packaging on target data of the damage event to generate a first block, the target data being used for recording event attributes and verification information of the damage event, and the verification information being used for verifying data integrity of data corresponding to the damage event; and storing the first block to the block chain. The technical problem that the authenticity of data is difficult to guarantee due to the fact that the vehicle state is tracked through archives or claim settlement records in the prior art is solved.

A vehicular camera includes a first shield made of metal and disposed to surround a circuit board. The first shield includes a first bottom surface portion, a second bottom surface portion disposed to be separated from the first bottom surface portion, and a connection portion connecting an entire periphery of the first bottom surface portion and an entire periphery of the second bottom surface portion. At least a first side surface portion, a second side surface portion, a third side surface portion, and a fourth side surface portion of the first shield are formed by a contiguously curved surface, and at least the first side surface portion, the second side surface portion, the third side surface portion, the fourth side surface portion, the first bottom surface portion, the connection portion, and the second bottom surface portion are formed by a contiguously curved surface.

A technique for using an onboard camera capable of day and night operation on an unmanned aerial vehicle (UAV) includes: traveling along a route of the UAV at night; and acquiring an aerial image with an onboard camera. The onboard camera includes: a sensor device for receiving photons and converting the photons into photoelectrons; a processor for processing the photoelectrons into an image file; a lens positioned adjacent to the sensor device for focusing the photons on the sensor device; and a filter positioned adjacent an outer surface of the lens. The filter can permit photons in the infrared light spectrum to pass to the lens, and attenuate at least a portion of the photons in the visible light spectrum prior to reaching the lens.

The invention discloses a road damage detection method based on an unmanned aerial vehicle and an intelligent networked automobile, and the method specifically comprises the following steps: (1) controlling the unmanned aerial vehicle and a vehicle-mounted camera to synchronously collect road surface images, inputting the collected road surface images into a road damage detection model through the unmanned aerial vehicle and the vehicle-mounted camera, and recognizing the road damage information of a current road section and the confidence coefficient through the road damage detection model; the damage information comprises a road damage type, a road damage coverage area and a road damage position; and (2) guiding the flight action of the unmanned aerial vehicle based on the low-confidence road damage position, so that the unmanned aerial vehicle flies towards the low-confidence road damage position, and returning to the step (1). Road damage identification is carried out based on the road surface images synchronously acquired by the unmanned aerial vehicle and the vehicle-mounted camera, more detail features of the road damage are captured by guiding the unmanned aerial vehicle to approach the road damage with low confidence, and the road damage can be identified more accurately.

The invention discloses a vehicle anomaly detection method, device and system based on cloud collaboration. The method comprises the following steps: acquiring RGB image data and depth image data of a vehicle in real time by adopting a vehicle-mounted camera and a radar; after receiving the data, the cloud end matches a corresponding scene image and abnormal event text description data, and carries out abnormal event early warning on a side end vehicle; the cloud end trains an RGB-D semantic segmentation model based on residual learning based on a large amount of image data; performing dynamic knowledge distillation on the trained RGB-D semantic segmentation model to obtain a new RGB-D semantic segmentation model, and transmitting weight parameters of the new RGB-D semantic segmentation model to the vehicle end; and the vehicle end performs reasoning according to the data collected in real time, detects an abnormal condition and makes a decision, broadcasts an abnormal event to the surrounding vehicle end, and uploads the abnormal event to the cloud end to assist in scheduling decision making.

The invention provides an aerial view feature generation method and device and electronic equipment. The method comprises the following steps: acquiring a plurality of acquisition images synchronously acquired by all vehicle-mounted cameras of a vehicle at the current moment; determining a bird's-eye view and an initial feature tensor thereof according to the plurality of collected images; generating a fusion feature tensor at the current moment according to the aerial view, the initial feature tensor and preset attention; and generating a target feature tensor of the aerial view at the current moment according to the historical feature tensor at the previous moment and the fused feature tensor. According to the generation mode, the fusion feature tensor is generated through the double attention of the spatial attention and the semantic attention, redundant calculation is remarkably reduced, overexposure or dark channel passing is inhibited through the spatial attention, high coupling with semantic categories is enhanced, and the accuracy of the fusion feature tensor is improved. Therefore, the robustness of generating the target feature tensor in extreme illumination scenes such as strong light, rain and fog is improved, noise interference is avoided, and the target feature tensor generation precision and generation efficiency of the aerial view are improved.

The present disclosure relates to a multi-mode vehicle window control method and device. The method combines voice recognition and computer vision technologies, detects a user's voice wake-up word using a vehicle-mounted microphone, turns on the vehicle-mounted camera to detect the user's face and head, analyzes the user's gaze, face pose, and head posture to estimate the user's attention region, and aligns the attention region with a vehicle body coordinate system. Intelligent control of a vehicle window is realized according to specific coordinates of an attention area on the vehicle window. Even if the user's face or eyes are not detected, the vehicle window may be operated accurately by determining the user's intention through the face or head pose.

The invention relates to an automatic parking method and device based on a vehicle-mounted camera, equipment and a medium. The method comprises the steps that first automatic parking path information and an environment sensing image of an automatic parking camera are obtained, and automobile position information is obtained through inversion according to the first automatic parking path information and the environment sensing image; calculating the image quality weight of each environment perception image in the environment perception overlapping area; based on the environment perception image and the automobile position information, an automatic parking environment perception panoramic image is generated in combination with image quality weight; recognizing an obstacle, and if the obstacle enters the real-time blind area, generating obstacle danger alarm information; and in response to generation of the obstacle danger alarm information, correcting the first automatic parking path information based on the obstacle danger alarm information to obtain second automatic parking path information. By adopting the method, high-precision environment perception and dynamic positioning can be realized, and the adaptability of complex scenes and intelligent detection of blind area obstacles are improved.