196 results about "Frame time" patented technology

The invention discloses a high-temperature airflow two-dimensional temperature field and velocity field synchronous measurement system and method based on laser-induced phosphorescence, and the system comprises phosphorescence particles, a low-frequency double-pulse laser, an image collection device, a synchronous controller, and an image processing device. The image processing device analyzes the gray intensity ratio of different wave band images acquired by the two PIV cameras at the same time, and combines a temperature response function calibrated by an experiment to realize inversion of a temperature field; meanwhile, a double-frame time-resolved image acquired by any PIV camera is subjected to cross-correlation calculation, particle displacement is extracted, and then a velocity field is reconstructed. According to the invention, synchronous acquisition of temperature and speed based on the same data source is realized, and the system has the remarkable advantages of simple structure, high measurement precision and wide application environment.

The invention relates to a video generation method based on time sequence similarity, and is applied to the field of video generation. Specifically, the video generation method based on the time sequence similarity comprises the following steps: acquiring generated video information; generating a key video frame sequence with frame rate information based on the text information, wherein the key video sequence is separated by a plurality of frame marks; performing recursive interpolation processing on the key video frame sequence, fusing front and back key frame features through a preset attention mechanism, and generating an initial intermediate frame between adjacent key frames; extracting visual features of a plurality of key frames and intermediate frames included in the key video frame sequence, calculating cosine similarity of the visual features of adjacent frames, and adjusting intermediate frame generation parameters based on the similarity to optimize inter-frame coherence so as to obtain an optimized intermediate frame; and combining the key video frame sequence with the optimized middle frame to generate a complete video clip which is consistent with the text information and has a coherent inter-frame time sequence.

The invention discloses an AI-based creative thinking auxiliary generation method and system, relates to the technical field of artificial intelligence, and solves the problem of inaccurate sound and picture matching in a traditional method by performing timestamp alignment and feature extraction on audio data and a visual image frame and calculating the correlation between the audio data and the visual image frame by using a cross-modal attention mechanism. According to the method, user eye movement track data is introduced, real attention points of a user are mapped into a visual sequence, and an optimized weight matrix is generated by constructing attention masks and fusing model attention weights, so that a generation result is more in line with perception key points of the user. And meanwhile, a feedback mechanism is established based on the synchronization error score, and when the sound and the picture are detected to be asynchronous, the visual frame timestamp can be dynamically adjusted, so that the self-adaptive correction of the content is realized. On the whole, the method has remarkable advantages in the aspects of improving modal alignment precision, enhancing user perception consistency and optimizing generation result naturalness.

The invention relates to the technical field of video image processing, and discloses a video image super-resolution enhancement method based on a generative adversarial network. The method comprises the following steps: segmenting a low-resolution video sequence, and analyzing frame timestamp information to generate a dynamic time axis containing key frame nodes so as to reflect video time change characteristics; then, in combination with the time axis and an image feature extraction system, feature mapping is carried out on the low-resolution frames, and a preliminary high-resolution image sequence with feature information is obtained; enhancing the preliminary sequence by using a generative adversarial network containing a generator and a discriminator in combination with a context-aware optimization technology to generate an enhanced sequence; and a machine learning algorithm is introduced to identify and classify different image quality region characteristic modes, and an intelligent identification rule base is established, so that an enhanced sequence is optimized. And finally, in response to user interaction, adjusting display parameters to realize personalized display, integrating a multi-dimensional analysis tool, calculating details of a specific region, and presenting a result in a visual interface, so that the video image quality can be improved.

The embodiment of the invention provides a digital video monitoring data transmission synchronization method and system, and relates to the technical field of digital video monitoring data transmission synchronization, and the method comprises the steps: receiving a video data stream and an external sensor data stream which is related to the content of the video data stream and has an independent stable time synchronization mechanism; identifying a visual event from the video data stream, and identifying a physical event associated with the visual event from the external sensor data stream; taking the timestamp of the physical event as a time anchor point, obtaining a visual original timestamp of the visual event, and calculating the time deviation of the video data stream according to the time anchor point and the visual original timestamp; based on the time deviation, correcting the frame timestamp of the video data stream by adopting an adaptive weighted average or filtering strategy to obtain a corrected timestamp; and fusing the corrected timestamps to obtain a global time reference. The reliability of the monitoring data and the accuracy of the analysis result can be improved.

The invention relates to the technical field of video detection, in particular to an anomaly detection method and system fusing large and small models and cooperating with cross-time domain perception. Comprising the steps of configuring a small model, a multi-modal large model and a cross-time domain parameter based on an electric power scene; acquiring a monitoring video stream, calculating a dynamic frame extraction frequency based on a scene change coefficient of continuous video frames of the monitoring video stream, extracting a frame sequence and recording a timestamp of each frame; inputting a frame sequence into the small model to obtain a candidate target, removing redundancy through non-maximum suppression, screening an effective target in combination with a single-frame confidence coefficient and an inter-frame time domain continuous overlapping rate, marking an alarm image and generating a preliminary analysis result; a time-domain-crossing video frame, power scene sensor data and environment data are collected according to a dynamic time window by taking an alarm image timestamp as a center, a visual time-domain feature and a power scene sensor time sequence feature are extracted, and a time-domain-crossing fusion feature is obtained through fusion. The problem of misjudgment and missed judgment caused by single-frame dependence in power scene anomaly detection is solved.

A signal generator may include a reference horizontal synchronization signal generation block which generates reference horizontal synchronization signals based on a number of clock signals per a horizontal time, a frame clock calculation block which calculates a first frame clock number based on a number of the clock signals per the horizontal time, a frame clock comparation block which calculates a clock offset by comparing the first frame clock number and a second frame clock number generated based on a number of the clock signals per a frame time, a clock distribution block which generates horizontal synchronization signals by distributing a number of the clock signals corresponding to the clock offset to the reference horizontal synchronization signals, and a vertical synchronization signal generation block which generates a vertical synchronization signal based on the horizontal synchronization signals.

The invention discloses an image acquisition method and device, electronic equipment and a storage medium. The image acquisition method comprises the following steps: acquiring a frame synchronization signal; and simultaneously outputting the frame synchronization signal to the plurality of acquisition devices based on a frame synchronization signal line, so that the plurality of acquisition devices acquire a group of synchronizable images. A plurality of acquisition devices are connected with a control chip through the same frame synchronization signal line, and frame synchronization signals are simultaneously output to the plurality of acquisition devices through the frame synchronization signal line, so that the plurality of image acquisition devices can perform image acquisition at the same triggering moment, and a group of synchronous images which are aligned during frame are obtained. According to the invention, the image synchronization between the synchronizable images is improved, so that if the synchronizable images are spliced, the jelly effect in the splicing process can be obviously reduced, and the acquisition requirement of the intelligent parking system on the high-time-sequence consistency image data is met.

A method of an optical sensor device includes: providing an optical sensor for receiving reflected light associated with a light emission unit to generate at least one sensed image; using a first exposure setting to make the optical sensor generate a first frame data during a first frame time period of a frame; when performing an exposure adjustment operation, using a second exposure setting to make the optical sensor generate a second frame data during a second time period of the frame neighbor to the first frame time period of the frame; and, generating a normalized digital signal corresponding to the first frame data based on the relation between the first frame data and the second frame data.

The invention relates to the technical field of artificial intelligence, can be applied to the fields of financial science and technology and medical science and technology, and discloses a video key frame extraction method, device and equipment and a medium. Then, a time-space relation graph of the video frames is constructed, nodes represent the video frames, and edge weights are jointly determined by inter-frame time proximity and visual feature similarity; performing feature propagation on the space-time relation graph by using a source domain pre-trained space-time graph neural network to obtain an initial importance score of each video frame; then, on the basis of scene characteristic indexes of a target video, through neural architecture search driven by a reinforcement learning strategy, topological structure parameters of the space-time diagram neural network are dynamically adjusted; and finally, recalculating the importance score of the video frame by using the adjusted space-time diagram neural network, and outputting a key frame sequence according to a scoring result, thereby improving the accuracy of key frame extraction and scene adaptability.

The invention relates to the technical field of communication interface conversion, in particular to a USB (Universal Serial Bus) to CAN (Controller Area Network) device and a transmission rate adjusting method, and the method comprises the following steps: acquiring a CAN bus load by monitoring a frame time interval of a sending frame and data traffic on a bus; the standard bit error rate is obtained by monitoring the proportion between the error frame and the data frame; generating an initial adjustment transmission rate value through weighted summation operation based on the CAN bus load and the standard bit error rate; according to the method, the CAN bus load condition, the bit error rate, the USB link characteristic parameters and the data communication characteristics are comprehensively considered, and the multi-dimensional input vector is established and input into the rate optimization prediction model, so that the dynamic optimization adjustment of the data transmission rate is realized, and the data transmission efficiency is improved. According to the scheme, the transmission pressure can be evaluated in real time according to the actual communication link state and the system performance, the rate is reasonably adjusted, the stability and efficiency of data transmission are remarkably improved, and the error rate and the link conflict risk are reduced.

The invention relates to the technical field of audio and video synchronization, in particular to a video call real-time audio and video synchronous monitoring system which comprises a frame time extraction module, a main time sequence locking module, a delay structure analysis module, a synchronous node generation module and a synchronous control instruction module. According to the invention, through real-time extraction and analysis of timestamp difference calculation of audio and video frames and establishment of a transmission delay interval comparison sequence, the time difference in audio and video transmission can be effectively identified, the monitoring accuracy of an audio and video asynchronization phenomenon is enhanced, and through real-time adjustment of timestamp offset, the synchronization accuracy of the audio and video in a playing process is ensured; in a dynamic network environment, the offset rate is monitored and adjusted in real time, the continuity and fluency of interactive experience are ensured, the synchronization state of the audio and video frames can be controlled more accurately by analyzing the offset difference value centralized distribution section and marking the synchronization fluctuation section, and the situation that the large-scale user experience is reduced due to synchronization error accumulation is avoided.

The invention discloses a video advertisement intelligent insertion method and system based on semantic segmentation and multi-modal context fusion. Through pixel-level semantic mask and multi-frame time sequence analysis, a space neutral area which can be used for advertisement embedding in a video is automatically identified, and background stability judgment is carried out in combination with indexes such as structural similarity and brightness change; and constructing a multi-modal context modeler, fusing a character emotion vector, a video rhythm vector and a scene structure vector, generating a context situation vector through a cross attention mechanism, and outputting an insertion suitability score. And when the score reaches a set threshold value and the neutral area meets the condition, the system executes advertisement generation and visual fusion operation to realize natural advertisement insertion consistent with the original video content style. The method is suitable for various content platforms such as short video and live broadcast, and experiments show that the click rate and the complete broadcast rate can be remarkably improved, and the jump-out rate is reduced.

The invention discloses a video quality evaluation method and system based on space-frequency combination and time sequence interaction, and relates to the technical field of computer vision, and the method comprises the steps: carrying out the standardization and data enhancement of an immersive video key frame; then, spatial domain and frequency domain double-path features are constructed through learnable Gabor convolution, two-dimensional Fourier transform and a logarithmic magnitude spectrum; space-frequency dynamic fusion is realized through bidirectional Cross-Attention, and a joint representation is generated; then, inputting Transform architecture modeling inter-frame time sequence dynamic and global dependence, and obtaining time sequence correlation characteristics; and finally, outputting frame-by-frame quality scores through learning weighted MLP regression, and aggregating the frame-by-frame quality scores into an overall quality score. According to the method, high-fidelity no-reference quality evaluation of immersive video distortion is realized through space-frequency joint modeling and time sequence interactive learning.

The application discloses a video instance segmentation method and system based on global feature enhancement, and belongs to the technical field of computer vision and deep learning, which comprises the following steps: inputting continuous video frames into a double-channel decoupling feature extraction module to obtain appearance and position features; inputting the two types of features into a tracker and a global feature memory updating module to dynamically update and obtain long-time sequence global context features; completing instance detection matching by the tracker, judging target state to obtain disappeared and newly appeared target queries; combining long-time sequence features to model current frame time sequence to generate enhanced features; finally, the tracker completes segmentation and tracking based on the enhanced features and the target queries, and outputs a segmentation mask sequence, an instance ID, a category ID and a tracking state. Through double-channel decoupling, double-memory block updating, multi-cost matching and multi-weight feature fusion, the application strengthens appearance feature representation and long-time sequence information utilization, and significantly improves segmentation accuracy and tracking robustness in complex scenes.

The invention provides a method and device for obtaining first frame time delay, and relates to the technical field of short video processing. The method comprises the following steps: judging whether a video is preloaded or not when being played in terminal equipment; if the video is preloaded when being played in the terminal equipment, determining that the time delay of the first frame of the video is 0; and if the video is not preloaded when being played in the terminal equipment, determining the first frame time delay of the video according to the video playing start time and the playing request time of the video. According to the method provided by the embodiment of the invention, the first frame time delay of the video can be conveniently and accurately determined.

The invention discloses a one-way link data integrity rapid verification method and system, and relates to the technical field of communication security, and the method comprises the steps: determining a whistle frame interval and a fingerprint sampling layout in a window according to a preset rule, sending a whistle frame, and forming an effective anchor point at a receiving side according to tolerance verification; segmenting the to-be-verified data according to the block length, generating a block-level rapid verification value, and verifying according to arrival; extracting sparse fingerprints on the data stream according to the fingerprint sampling layout and sending the sparse fingerprints, and performing recalculation and comparison at corresponding positions; and judging that the window does not pass when the whistle frame intervals are accumulated in a border crossing manner or effective anchor points are insufficient, otherwise, establishing an anchor neighborhood by using the effective anchor points, counting expected sampling hit and dissociation, synthesizing whistle finger coupling steady quantity, and judging that the window passes when the block-level rapid verification is passed, the sparse fingerprints are consistent and the whistle finger coupling steady quantity is greater than a threshold value. Through combination of a whistle frame time sequence, block verification and fingerprint sampling in a time window, one-way link transmission consistency evaluation is realized, and the exception screening and tampering detection capabilities are improved.

The invention relates to the technical field of data processing, in particular to a game lag analysis method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining the current frame time consumption of a target game program in a current game frame based on a frame interval interface; determining lag information of the current game frame based on the current frame time consumption and adjacent frame time consumption of an adjacent game frame before the current game frame; under the condition that the lagging information of the current game frame represents that the current game frame is lagged, obtaining function consumed time corresponding to at least one function group based on a consumed time instrumentation function corresponding to the at least one function group; and based on the function time consumption corresponding to the at least one function group, determining a lag factor corresponding to the current game frame. The game lag analysis efficiency can be improved.

The invention provides a video enhancement display method and device, a display system and electronic equipment. The method comprises the following steps: acquiring image quality data, inter-frame motion vector data, video code stream data and mapping search data; processing the video code stream data and the image quality data by using the current frame airspace network model to obtain weight parameters; performing fusion processing based on the mapping search data and the weight parameters to obtain dynamic mapping search data, and obtaining current frame enhanced image data according to the dynamic mapping search data; processing historical data in the inter-frame motion vector data and the video code stream data by using a historical frame time domain network model to obtain historical frame enhanced image data; and obtaining video code stream data after image quality enhancement according to the current frame enhancement image data and the historical frame enhancement image data. According to the scheme, the low-bit-rate image quality performance in a severe network environment can be improved, and meanwhile, the native defect that a YUV420 format is compared with an RGB format or a YUV444 format, and pseudo-color exists at a high-frequency edge can be overcome.

The invention discloses a clock signal generation method, a module and a display device. The clock signal generation method comprises the following steps: within a frame time (F0), when an enable end (EN) provides an effective enable signal and clock indication ends (CPV1 and CPV2) provide effective clock indication signals, obtaining a time sequence for generating a clock signal; and when the generation of the clock signal is stopped, the timer (J1) performs timing, and the timing sequence for generating the clock signal again is obtained according to the timing time obtained by the timer (J1). Clock signal ends (CLK1, CLK2, CLK3, CLK4, CLK5 and CLK6) can be opened in any line according to needs, any line display of the display panel is achieved, and power consumption reduction and multi-scene application of the display panel are achieved.

The invention discloses a cross-device video synchronous display method, which relates to the technical field of video display, is used for solving the problems of video playing interruption and user experience reduction, and is used for detecting operation behavior data of a field terminal and quantifying the influence of the operation behavior data on the synchronization stability by synchronizing clock references at two ends and establishing a synchronous clock. Analyzing data generation characteristics, generating a drift index after detecting a drift distance of a synchronous clock, judging whether to trigger a transmission regulation and control mechanism by combining the data generation characteristics, and when entering the transmission regulation and control mechanism, acquiring network state data of a field terminal and receiving buffer data in a remote terminal; according to the method, data sending and reading time sequences of a field terminal and a remote terminal are adjusted, frame timestamps at two ends are detected after adjustment, whether a transmission regulation and control mechanism is triggered again or not is judged according to the frame timestamps, self-adaptive synchronous control under network fluctuation is achieved, and frame-level synchronization and playing continuity of a cross-device video in a variable environment are kept.

The invention discloses a cross-platform VR resource performance evaluation and compatible operation method and system, and the method comprises the steps: building a VR resource performance evaluation model based on the performance evaluation of a CPU and a GPU, and the model comprises a CPU score, a GPU score, a weight coefficient and a performance stability correction factor of a current device; the CPU score is obtained through calculation of inter-process communication and a context switching number in a current equipment system environment, the GPU score is obtained through calculation of an actual computing power value and rendering delay which are obtained through multiple iterations of a standard GLSL matrix multiplication in the current equipment system environment, and the performance stability correction factor is determined according to frame time when VR resources are operated by current equipment; when the VR resources need to be operated, the evaluation score of the VR resources operated by the current equipment is calculated through the performance evaluation model, and the corresponding configuration parameters are allocated to operate the VR resources. According to the invention, the fluency and stability of the VR picture during operation can be ensured, and the user experience is improved.

The embodiment of the invention provides a streaming media data transmission method and device, equipment and a medium. In the method, a request for a first data block of streaming media data is received from a first device. The first data block is associated with a first frame of the streaming media data at the first device, and the first data block includes at least a media presentation description (MPD) associated with the streaming media data, audio data associated with the first frame, and video data associated with the first frame. Further, the first data block is sent to the first device. In this way, the first frame time can be reduced, and audio and video data misplacement can be prevented.

The present application relates to a smoke fire detection method based on feature matching and multi-frame time sequence fusion, which is suitable for highway fire detection scene. The method first screens out foreground change pictures based on the steady-state entropy change of video frame pixels. Then, the color and texture features of smoke fire are matched using the fast flooding algorithm to screen out candidate pictures from the foreground pictures. Next, a cache queue is established to store the candidate pictures and their timestamps, and the multi-frame time sequence image data in the queue is sent to the detection model based on the preset trigger condition. Finally, the multi-frame time sequence fusion smoke fire detection algorithm model extracts features and analyzes the time sequence fusion of the input multi-frame images, and outputs the final fire and smoke detection results. The present application realizes efficient detection through low-power cameras, reduces false alarm rate, improves complex environment monitoring distance, and has lower power cost.

The application relates to the technical fields of multimedia image processing, GPU computing power scheduling and soft power-on resource optimization, and discloses a resource occupation prediction method in a video special effect processing process, which is executed by a terminal built-in processor and comprises the following steps: collecting a video special effect frame time interval, a GPU rendering pipeline thread occupation ratio and a video memory fragment distribution ratio; performing dimensionless normalization processing on the video special effect frame time interval to obtain a special effect frame time normalization factor; counting a special effect superposition level; and calculating a special effect time coupling factor, a pipeline blocking loss factor and a total resource occupation prediction value and outputting the total resource occupation prediction value. The application solves the problem of large prediction deviation in the prior art, realizes accurate prediction through a core innovation point, guarantees reasonable allocation of video special effect rendering resources, and improves rendering stability.

The invention discloses a multi-screen interaction real estate display method based on a cave and an LED, and belongs to the technical field of vehicle-mounted electronics, and the method comprises the steps that a user interactively generates an operation item at a Pad end, analyzes a request, generates a rendering instruction, renders display content through Babylon.js, counts frame time and delay, judges whether a synchronization difference value between screens exceeds a threshold or not, and executes an adjustment strategy. The technical problems of synchronous control and space consistency rendering of multiple independent view angle LED screens in multi-frame rendering are solved, a three-view angle independent rendering mechanism among the multiple screens is achieved, stable and synchronous multi-screen content is ensured, a real-time Pad control and state response mechanism is supported, and the method and the device have the advantages of being simple in structure, convenient to operate and high in practicability. Smooth user operation and visual feedback are improved, and a modular system architecture is convenient to deploy and expand and adapts to various display environments and resolution specifications.

Disclosed herein are system, method, and computer program product embodiments for performing Synchronization Single Block (SSB) transmission using a number of SSB beams. An embodiment operates by determining a SSB index for a SSB based on a candidate position in a set of candidate positions and the number of SSB beams. The embodiment determines a shift value for the SSB index based on the candidate position and the number of SSB beams. The embodiment determines a frame timing for the SSB based the SSB index and the shift value for the SSB index. The embodiment then transmits, by radio front end circuitry, the SSB to a user equipment (UE) based on the frame timing for the SSB.

The embodiment of the invention provides a live broadcast stream pushing method and device, computer equipment, a computer readable storage medium and a computer program product, and belongs to the field of network live broadcast. The live broadcast stream pushing method comprises the following steps: in response to a configuration switching instruction, determining an end timestamp of a currently pushed initial live broadcast stream; determining a start timestamp of the target live broadcast stream according to the end timestamp, the start timestamp being after the end timestamp, and a time interval between the start timestamp and the end timestamp being equal to an inter-frame interval between adjacent video frames of the initial live broadcast stream; and generating a target live broadcast stream by taking the start timestamp as a first frame timestamp, and pushing the target live broadcast stream to a streaming media server, so that an audience end pulls the target live broadcast stream from the streaming media server, finishes playing the initial live broadcast stream at an end timestamp, and plays the target live broadcast stream by taking the start timestamp as a starting point. According to the technical scheme, the watching experience of audiences and the live broadcast experience of an anchor can be improved.

The invention provides a naked eye 3D end-to-end real-time communication method and system, and relates to the technical field of 3D communication, and the method comprises the steps: a transmitting end collects two video streams and a single audio stream of a target scene, synchronizes the two video streams and the single audio stream, carries out the frame-by-frame image splicing of the two synchronized video streams, and carries out the frame-by-frame image splicing of the two synchronized video streams; obtaining three queues of image frames, audio frames and timestamps, and respectively sending the queues to a receiving end item by item according to the queues; the receiving end synchronizes the received image frame and audio frame based on the timestamp, and performs naked eye 3D presentation of the target scene on the synchronized image frame and audio frame; according to the naked-eye 3D end-to-end communication system and the naked-eye 3D end-to-end communication method, lowest universal hardware equipment is used, and an innovative data processing flow and an optimization algorithm are combined, so that the naked-eye 3D end-to-end communication experience with high quality, low crosstalk and a wide comfortable area is realized while the cost and the complexity are greatly reduced; the core problems of high hardware cost, complex system, poor viewing experience, high technical threshold and the like in the prior art are effectively solved.

The invention discloses a video facial expression recognition method based on a fuzzy time refinement network, is applied to the technical field of computer vision and artificial intelligence, and aims to solve the problems that in the prior art, the expression time sequence dynamic state is difficult to capture, the processing feature fuzziness is low, and the refinement category recognition precision is low. The method comprises the following steps: preprocessing video frames; extracting spatial features by adopting ResNet-18 (ResNet-18); modeling inter-frame time sequence dependence through LSTM; dynamically weighting key frame features by using a fuzzy attention module (FAN) in combination with Gaussian, triangle and Sigmoid membership functions; carrying out the optimization of feature clustering through the combination of cross entropy loss and TriCenter Loss; outputting an expression category; by adopting the method, the video facial expression recognition accuracy can be effectively improved.