29 results about "Dynamic resolution" patented technology

The invention discloses a multi-scene micro garbage real-time detection method and a multi-scene micro garbage real-time detection system, and aims to solve the defects of an existing garbage detection method in the aspects of small target identification, environmental adaptability and system integration. According to the method, on the basis of an improved YOLOv8 architecture, a Transform module and an efficient channel attention mechanism are fused, and the tiny target feature extraction and multi-scale information fusion capability is enhanced. The system adopts dynamic resolution reasoning, INT8 quantitative compression and time-space domain post-processing, so that the detection precision and the reasoning efficiency are remarkably improved. Experiments prove that the system effectively improves the small target recall rate and environmental adaptability in a garbage detection task, comprises eight corresponding modules, realizes full-process automatic detection, has relatively high real-time performance and automation level, is suitable for various application scenes such as smart city environment monitoring, and has important practical application value.

The invention provides a road preview method and system based on a point cloud dynamic resolution allocation algorithm, and belongs to the field of automatic driving and intelligent traffic systems. The method comprises the following steps: acquiring an image pair acquired by a binocular camera, and preprocessing the image pair; generating a depth map of the scene based on the preprocessed image pair, and dividing the depth map into a plurality of regions of interest in a depth dimension; for each region of interest, calculating the importance weight of the region of interest based on the depth gradient and the motion vector; dynamically distributing the point cloud resolution of the region through a mapping function according to the depth value of the region of interest and the importance weight corresponding to the depth value; and based on the distributed point cloud resolution, generating point cloud data of dynamic resolution for road preview and path planning of the vehicle. According to the method, the problems of resource waste and poor real-time performance caused by full-scene uniform sampling of traditional binocular vision are solved, and the precision and efficiency of automatic driving road preview are remarkably improved.

A computing system for generating a gain map-based enhanced High Dynamic Resolution (HDR) image receives an HDR image comprising a plurality of pixels, each pixel having one or a plurality of brightness values for each of a plurality of color components, applies at least a first tone mapping algorithm to each pixel in the HDR image, generates a gain map using the HDR image and the SDR image, generates a gain map-based enhanced HDR image based on the SDR image and the gain map, and generates an output based on the gain map-based enhanced HDR image.

The invention provides a 3D laser SLAM method and device based on optimized loopback detection and a medium, and relates to the technical field of simultaneous positioning and mapping of robots, and the method comprises the following steps: (1) a data preprocessing step: receiving original data of an IMU and a laser radar Lidar, and carrying out the denoising and time synchronization processing; (2) a feature extraction and map construction step: extracting angular point and surface point features from the preprocessed data, performing pre-integration on IMU data to obtain an initial pose, and performing registration on a current Lidar point cloud and a local map to construct a global map; (3) loopback detection: generating an enhanced descriptor based on the key frame point cloud, and constructing a KD-Tree structure with dynamic resolution for storage and indexing; and carrying out rough search on loopback candidate frames by inquiring the KD-Tree, carrying out two-stage pose matching on the candidate frames to confirm loopback, and dynamically distributing the weight of loopback constraint according to the environmental complexity. The loopback detection success rate can be improved, and dynamic scene mapping drift is reduced.

The invention discloses an edge end real-time target detection method based on multi-granularity attention fusion and space-time consistency constraint. The method aims at solving the problems that existing edge end target detection does not give consideration to real-time performance and precision, and video sequence detection consistency is poor. The method comprises the following steps that S1, a multi-source data set is constructed and preprocessed; s2, designing and optimizing a lightweight multi-granularity feature extraction backbone network; s3, implementing a dynamic multi-granularity attention fusion module, and performing adaptive fusion on multi-granularity features; s4, enhancing the video sequence detection consistency through a predictive spatio-temporal feature alignment module and a spatio-temporal consistency loss function; s5, constructing a detection head and a multi-task loss function; s6, performing model training; and S7, carrying out edge device adaptation and reasoning acceleration by adopting quantitative perception training, dynamic resolution adjustment, optimized non-maximum suppression and other methods. According to the invention, the precision, the time sequence consistency and the real-time performance of edge end real-time target detection are obviously improved, and the method has the characteristic of high efficiency.

A method for reducing artifacts in streaming video implemented by a computing device involves determining whether a video quality assessment score for a current segment of a channel of a video stream with a first resolution and a first bit rate meets a quality threshold, replacing the current segment with a replacement segment with a lower resolution than the first resolution, in response to the current segment failing to meet the quality threshold, and publishing the replacement segment at the first bit rate as part of the video stream.

An example device for retrieving media data includes a memory configured to store video data; a video decoder configured to decode the video data; and one or more processors implemented in circuitry and configured to: determine that a media presentation includes first video data at a first spatial resolution and second video data at a second spatial resolution, the second spatial resolution being different than the first spatial resolution; receive a first portion of the first video data at the first spatial resolution for a first playback time; send the first portion of the first video data at the first spatial resolution to the video decoder; receive a second portion of the second video data at the second spatial resolution for a second playback time later than the first playback time; and send the second portion of the second video data at the second spatial resolution to the video decoder.

A mechanism for processing video data is disclosed. The mechanism includes determining to select one or more adaptive scaling filters. A conversion is performed between a visual media data and a bitstream based on the adaptive scaling filters.

The present disclosure relates to a static graph mode graph generation system supporting dynamic resolution. The system comprises: an original logic graph construction component, for a first specific graph generation task, tracking original computing logic by executing a construction function of a graph to construct an original logic graph; a logic graph optimization component, forming a first logic graph for the constructed original logic graph; a node insertion component, inserting a communication node and a runtime control node required by distributed computing for the first logic graph to generate a first runtime logic graph for multi-device collaboration; a runtime plan generation component, generating a first runtime execution plan based on a data dependency relationship of the first runtime logic graph; and a runtime initialization component, initializing a first specific graph runtime instance according to the first runtime execution plan to complete dynamic allocation of computing resources and configuration of an execution environment.

The invention relates to the field of image communication, in particular to a mobile terminal video stream data adaptation processing method based on an external camera, which comprises the following steps: an acquisition terminal ensures that a source frame rate is stable through the external camera with an IMU (Inertial Measurement Unit) in combination with frame rate monitoring and dynamic caching; the edge node adopts parallel preprocessing, a lightweight model and adaptive coding to compress single frame processing delay; the transmission link realizes fragmentation transmission, priority scheduling and multi-path redundancy based on UDP + RTSP, HTTP / 3 and SRT protocols; the terminal side reduces the decoding load through pre-decoding, fragmentation caching and dynamic resolution adaptation; and the full-link routing collaborative dispatching center monitors the indexes in real time and triggers a grading, degrading and fault switching mechanism. According to the technical scheme, high-stability and low-delay video stream processing with the end-to-end delay smaller than or equal to 150 ms, the frame rate fluctuation within + / -1 fps and the lagging rate smaller than or equal to 0.5% is achieved, and the immersive video experience in weak network and high load scenes is remarkably improved.

The application discloses a dynamic resolution ultrasonic phased array haptic generation device and a control method, relates to the technical field of ultrasonic haptic feedback, and realizes the software adjustment of the ultrasonic haptic focus size through an EDM beam forming algorithm, thereby breaking through the limitation of the traditional DAS method which is limited by hardware. Users can dynamically select a high resolution mode or a high radiation force mode according to specific application scenarios, and the flexibility and reality of haptic interaction are significantly improved. The system structure is compact, all adjustments are completed through software, hardware does not need to be changed, and the system is convenient to integrate into intelligent automobile central control, AR / VR headgear, interactive exhibition stands and other equipment, so that more rich and adaptive haptic experiences are provided for human-computer interaction. Under the premise of not changing the hardware structure, the system optimizes the phases and amplitudes of all channels of the ultrasonic array through the software algorithm of the upper computer, and cooperates with the hardware logic control of the FPGA controller to realize the dynamic control of the spatial resolution of the haptic focus and the generation of multiple foci.

This invention discloses a visual-tactile sensor based on high-density feature design and its image generation and tracking method. Addressing the problems of matching ambiguity and low tracking density caused by homogenized marker points in existing technologies, this invention first generates a globally unique feature pattern through an iterative algorithm with dual constraints in the spatial and color domains. Then, it utilizes adaptive field-of-view adjustment to compensate for feature distribution under different camera positions. This pattern is embedded in the sensor's tactile perception layer. During tracking, this invention employs a two-level cascaded matching logic, combined with reference frame modeling, dynamic resolution mechanisms, and mean normalization processing, to achieve displacement capture from pixel-level coarse matching to sub-pixel-level super-resolution. This invention significantly improves the sensor's displacement field tracking density, effectively eliminates feature confusion under large deformations, and enables high-precision perception at the full-field pixel level, providing a reliable high-density tactile feedback foundation for the refined operation of robots.

A video source device for wireless display sharing, comprising: an encoder designed to dynamically switch between encoding a full video frame into a first bitstream with a first resolution and a video subframe into a second bitstream with a second resolution, the second resolution being higher than the first resolution; a processing circuit arrangement designed to decide between encoding the full video frame and the video subframe based on an amount of available wireless transmission bandwidth, a number of pixels in a modified area of ​​the full video frame, spatial complexity of a modified area of ​​the full video frame, temporal complexity of a modified area of ​​the full video frame, and / or an area-change category of the full video frame; and a transmitter designed to wirelessly transmit the first bitstream and the second bitstream to a video sink device.

The embodiment of the invention relates to enhanced HDR image generation based on a gain map. A computing system for generating an enhanced high dynamic resolution (HDR) image based on a gain map receives an HDR image comprising a plurality of pixels, each pixel having one or more luminance values for each color component of a plurality of color components; applying at least a first tone mapping algorithm to each pixel in the HDR image; generating a gain map by using the HDR image and the SDR image; generating an enhanced HDR image based on the gain graph based on the SDR image and the gain graph; and generating an output based on the gain map-based enhanced HDR image.

The invention provides a dynamic resolution visual language model training method, a dynamic resolution visual language model detection method and dynamic resolution visual language model detection equipment. The dynamic resolution visual language model training method comprises the steps of obtaining a multi-modal document data set and a plurality of query text feature vectors; training a preset deep learning model to enable the deep learning model to detect each document image in the training process to generate a plurality of visual area maps with different resolutions corresponding to each document image, and extracting and fusing each visual area map to obtain an image feature vector, target loss is calculated based on the image feature vectors and the corresponding query text feature vectors to update model parameters of a deep learning model, and a trained deep learning model is obtained; and taking the deep learning model as a dynamic resolution visual language model for retrieving a document page corresponding to the query text feature vector from a plurality of document images. According to the method, the problem that the retrieval precision is limited due to the fact that complex layout and visual details in a document are ignored due to fixed-resolution input in a traditional method can be effectively solved.

The application discloses a lightweight target detection method, and particularly relates to the technical field of target detection. Firstly, the input image is preprocessed, and low-computational and rich-semantic features are extracted through a parallel convolution branch. Then, an ICAneck lightweight backbone is adopted, and a separable convolution and a coordinate attention are combined to extract semantics. A strategy selection model is constructed, and according to the target scale, the definition and the small target density, switching is carried out between the fixed and dynamic resolution-channel strategies, so that the resolution and the number of channels are finely controlled. In stage 2-4, an incremental ICAblock is used for deepening abstraction. In the fusion stage, a proportional attention and a channel alignment module are introduced to integrate scale features, and a lightweight detection head is used to output the category and the frame. Through joint training of sparse regularization and multi-task loss, the calculation and the memory consumption are reduced, the accuracy of small targets is ensured, and the edge real-time deployment is adapted.

The invention discloses an image processing method and device, a storage medium and a processor. According to the scheme, an original image of the surrounding environment of a vehicle is collected, downsampling processing is carried out on the original image, and a preview is generated; segmenting the preview into a plurality of image areas, and calculating image entropies of all pixels in each image area; determining the region type of the corresponding region in the original image according to the image entropy of each image region; the region type comprises a plurality of salient regions of different grades, and the grades of the salient regions are in positive correlation with the image entropy; adjusting the resolution of a corresponding region in the original image according to the region type, and outputting the adjusted image as a target image; the resolution ratio of the corresponding region is positively correlated with the grade of the salient region corresponding to the corresponding region. Differentiation processing is carried out on the image through a dynamic resolution control mechanism, the computing power resource utilization rate of the intelligent driving system is improved, and the operation cost of the intelligent driving system is remarkably reduced.

The invention relates to the field of image resolution adjustment, in particular to a dynamic resolution adjustment method and system for a digital oil painting. The method comprises the following steps: identifying an input real-time image, calculating the pixel distribution density of the image, and performing overall scene composition analysis to obtain scene description information; performing oil painting style matching according to the scene description information, and extracting a style scale parameter set; performing digital optimization rendering on the global brightness optimization image according to the style scale parameter set, and performing adaptive region division to obtain a plurality of oil painting region frames; calculating the number of semantic elements and element density distribution of the oil painting region frame to obtain the rendering complexity of each region; and carrying out regional dynamic resolution adjustment according to the rendering complexity, carrying out global image optimization, and constructing a resolution-adjusted digital oil painting. According to the method, the detail definition of converting the real-time image into the digital oil painting is improved, and the artistic expressive force and ornamental value of the converted image are enhanced.

Methods, systems, and devices for wireless communication are described. A user equipment (UE) may dynamically indicate a resolution change to a display of the UE during a video call. For example, a first UE may communicate a configuration message with a second UE to establish a video call between the first UE and the second UE and indicate a first value for a resolution of a display of the first UE. During the video call, the first UE may identify a change to the resolution of the display and may transmit a message to the second UE that indicates the change to the resolution. In response to receiving the message, the second UE may encode one or more packets including video information for the video call according to a second value for the resolution and transmit the one or more packets to the first UE.

The invention provides a lightweight attitude estimation method based on dynamic resolution and structural re-parameterization. The lightweight attitude estimation method comprises the following steps: step 1, recognizing a human body core area, accurately quantifying a motion blur degree, dynamically correcting a decision threshold by combining a human body proportion, adaptively selecting resolution based on multi-dimensional parameters, and outputting frame data of adaptive resolution; 2, constructing a backbone network adaptive to attitude estimation, completing feature extraction, sub-network connection and reasoning optimization, and outputting a refined feature map; 3, based on the refined feature map output in the step 2, joint point heat map prediction, position positioning and result optimization are completed through a multi-stage posture estimation sub-network, and finally a human body posture estimation result matched with an original input frame is generated. According to the method, key joint points of the human body can be accurately detected and positioned, limb structures are reasonably connected, the reasoning speed can be remarkably increased, resource consumption is reduced, and the method can be successfully adapted to low-computing-power scenes such as embedded equipment and mobile terminals.

This invention provides a method, apparatus, device, and storage medium for adaptive rendering of large screens, belonging to the interdisciplinary field of intelligent connected vehicles and digital twins. The method includes: acquiring the resolution, refresh rate, and color gamut parameters of the large screen in real time; regenerating a configuration file when parameter changes are detected and trigger preset conditions; dynamically adjusting the resolution and mapping the color gamut according to the configuration file; determining a corresponding rendering strategy based on the adjusted resolution; and monitoring system resource utilization in real time, implementing the determined rendering strategy with different rendering precisions based on different system resource utilization rates. Through the technical solution of this invention, the problem of inconsistent rendering effects on large screens of different levels can be solved by combining resolution scaling and color gamut mapping strategies.

The application discloses a dynamic resolution rendering method and device, electronic equipment and a readable storage medium, and relates to the technical field of computers. The resolution is adjusted by resampling and rendering on a rendering texture, a new size of rendering picture is not generated, a large amount of rendering resources is avoided, and the purpose of saving resources is achieved. The method comprises the following steps: generating a target scaling ratio and a to-be-adjusted resolution; adjusting the rendering texture according to the to-be-adjusted resolution, and adjusting the size of the camera viewport of the scene camera of the animation scene according to the target scaling ratio; rendering the animation scene by using the adjusted camera viewport and the adjusted rendering texture, and obtaining a first rendering picture; performing scaling sampling rendering on the adjusted rendering texture and returning to a color buffer, and rendering the color buffer by using the interface camera of the animation scene, and obtaining a second rendering picture; and superimposing the second rendering picture on the first rendering picture to generate a target rendering picture.

The invention discloses a ground penetrating radar target identification method based on cross-modal dynamic resolution. For the problem of feature blurring caused by modal information splitting and resolution fixing, a dynamic resolution optimization and cross-modal attention fusion cooperation mechanism is provided: image degradation features are analyzed through a time sequence convolutional network, multi-scale resolution parameters are dynamically generated, and target density adaptive feature enhancement is realized; a cross-modal attention module is designed, intensity and Doppler features are decoupled in a feature pyramid, dual-modal complementary fusion is realized through channel weighting and space focusing, and cross-scale semantic interaction is optimized based on a bidirectional feature pyramid. By integrating a lightweight target detection architecture and a multi-task cooperative training mechanism, the inference efficiency is optimized while the recognition accuracy of the tiny target in a complex scene is guaranteed, and the method is particularly suitable for sensing scenes such as intelligent driving, geological disaster early warning and the like which have strict requirements on timeliness.

A method for raw seismic data inversion includes receiving raw seismic data acquired over an underground formation, receiving an initial velocity model of the underground formation, performing a dynamic resolution full waveform inversion, DR-FWI, on the raw seismic data so that a tomography component of a velocity gradient G is compensated to generate a compensated tomographic component while a diving wave component and a migration component are preserved, outputting an updated velocity model based on an illumination compensated velocity gradient G′, which is calculated based on the compensated tomographic component), and locating natural resources in the underground formation using the updated velocity model updated by the DR-FWI.

This invention discloses a multimodal event extraction method and system based on iterative visual verification, belonging to the interdisciplinary field of natural language processing and computer vision. The method generates an initial event list using a large multimodal model, and uses an optimized dynamic resolution visual verifier for inspection and feedback, driving the iterative process and enhancing generator performance, forming a closed-loop optimization mechanism of "generation-verification-correction." It provides two verifier training strategies: adjusting the number of trainable parameters to only 0.1%-2% of the original model, resulting in extremely low computational resource consumption; and a reinforcement learning strategy to further improve performance, suitable for scenarios with extremely high accuracy requirements. By training on a weakly aligned random perturbation dataset, the model can learn to detect incompleteness, type errors, and hallucination elements in the event list, and output structured feedback containing four types of error information, effectively solving the incompleteness and hallucination problems of large language models in multimodal event extraction.

This invention discloses a multi-dimensional perceptual gaze-point rendering method, system, and medium. The multi-dimensional perceptual gaze-point rendering method is characterized by the following steps: S1, acquiring the user's eye-tracking data in real-time within a virtual reality environment; S2, dividing the rendering sequence into saccade windows, recovery windows, and stable gaze windows; S3, constructing a multi-dimensional visual perception model that integrates saccade sequence features; S4, acquiring the perception critical frequency and mapping it to a resolution scaling factor to guide rasterization operations in the graphics pipeline; S5, invoking the resolution scaling factor and performing dynamic resolution rendering in the graphics rendering pipeline based on the resolution scaling factor. The system includes a data acquisition module, an event detection module, a model calculation module, a rendering scheduling module, and a graphics drawing module. This invention is rationally designed, effectively utilizing computing resources, improving the rendering system's frame rate, and enhancing the user experience.

This application discloses a video optimization method, a playback device, a gateway device, a storage medium, and a system. The method includes: determining video parameter data corresponding to the current video stream; calculating the resolution based on the video parameter data to determine a target resolution; and sending the target resolution to the gateway device so that the resolution of the video stream to be transmitted most recently received by the gateway device is the target resolution. In this way, after sending the target resolution to the gateway device, the resolution of subsequent video streams to be transmitted can be the target resolution. By integrating a software development kit (SDK) into the playback device, the resolution of the video stream can be dynamically adjusted based on the video parameter data. This not only effectively alleviates video stuttering caused by poor network conditions but also makes the dynamic resolution adjustment more precise and reasonable, thus improving video quality.

The invention provides a resolution adaptive mapping method and device for display type interaction equipment, and relates to the technical field of data interaction, and the method comprises the steps: respectively collecting resolution parameters and screen diagonal length parameters of source equipment and target equipment; in combination with the resolution parameter and the screen diagonal length parameter, establishing a resolution corresponding relation between the source device and the target device; determining a basic compression ratio parameter according to a resolution ratio corresponding relation; performing performance correction on the basic compression ratio parameter according to the graphic processing capability parameter and the network bandwidth upper limit parameter of the target equipment to obtain a performance correction compression ratio parameter; and based on the performance correction compression ratio parameter, carrying out zooming and coding processing on the display content output by the source equipment, and generating display data adaptive to the target equipment. According to the invention, dynamic resolution self-adaptive adjustment can be realized in combination with physical characteristic parameters of equipment.