35 results about "Interframe correlation" patented technology

The invention provides a target detection identification method and system in a low altitude and sea surface environment. The method comprises steps of establishing a space virtual reference coordinate system and carrying out self-calibration; for different measurement conditions, using corresponding coordinate conversation methods, allowing data of measurement points and targets to be establishedin the space virtual reference coordinate system; calculating all geometrical parameters of each target and coordinates of the target; through two radars in different heights, carrying out self-calibration and blind supplementation; by use of a de-noising method of interframe correlation, processing radar signals; and carrying out information fusion processing on multi-source target data in the radars and carrying out target detection and tracking. According to the invention, by use of dynamic self-calibration technology, and adaptive detection and recognition technology, strong sea clustersare inhibited; positioning precision and recognition rate of the targets are improved; target detection ability for observing sea area during day and night in a severe weather environment is improved;and effective detection, tracking, recognition and law enforcement monitoring evidence obtaining for small targets on the sea surface and low-altitude small targets like unmanned aerial vehicles areachieved.

The invention relates to an image and video processing method and system, in particular to a method and system for rapidly detecting static superimposed text in an online video stream. The static superimposed text detection method utilizes inter-frame correlation information and wavelet domain modeling and other methods, which can effectively remove moving text and background areas, and retain the static superimposed text area. The method can realize the rapid detection of the static superimposed text position in the online video stream. At the same time, an online video stream retrieval system is constructed based on the static superimposed text detection method. In this system, different parameter families are used for fast text detection on each user terminal, and the results are converted into text streams through the OCR control. After each user terminal transmits the text stream to the centralized retrieval server for integration, a multi-time granular retrieval function for each channel and a content-based quick browsing function for each channel can be provided. The present invention can realize the functions of synchronous analysis, indexing, retrieval and browsing of multiple online video streams with multiple qualities without infringing copyright, and does not need to establish special servers for various video streams.

The invention relates to a video detection technology and discloses subtitle detection method and device as well as background recovery method and device, wherein the subtitle detection method comprises the following steps of: acquiring the probability of a pixel region in a video frame belonging to a smooth background; determining the probability of the pixel region belonging to a still texture by using an interframe correlation coefficient; acquiring the probability of the pixel region belonging to a dynamic texture; and determining whether the pixel region belongs to a roll subtitle regionor not according to the probability belonging to the smooth background, the probability belonging to the still texture and the probability belonging to the dynamic texture of the pixel region. By using the technical scheme provided by the embodiment of the invention, interframe information can be used for detecting subtitles of a video.

The invention discloses a video SAR moving target detection method based on image area accumulation, which mainly solves the problem of unsteady detection of the existing video SAR moving target. The realization scheme is as follows: 1) Design the accumulation window and perform regional accumulation on the video SAR image sequence; 2) Determine the accumulation threshold and perform image reconstruction on the accumulation result; 3) Binary segmentation of the reconstructed image; The image after value segmentation carries out the size statistics of the connected domain and retains the connected domain whose size is within the range of 0.4 times the total number of pixels occupied by the target and 2 times the total number of pixels occupied by the target; 5) performs inter-frame correlation on the processed image of the connected domain Processing removes non-target shadows and completes moving target detection. The invention effectively suppresses the probability of false alarms and missing alarms and improves detection performance by performing regional multi-frame joint detection on video SAR images, and can be used for tracking and real-time detection of video SAR moving targets.

The invention discloses a video sequence reconstruction method based on compressed sensing. An encoding end separates an original video sequence into two types of frames, i.e., key frames and non-key frames, and measurement is performed respectively by use of different sampling rates. At a decoding end, different video sequences are subjected to performance judgement of two different algorithms, i.e., motion estimation / compensation prediction and optical flow method prediction, and then through combination with a comparison result, all the non-key frames are subjected to good-performance algorithm reconstruction by use of inter-frame correlation . When a video is processed, the amount of data needing to be sampled is small and the quality of the recovered video is good. Compared with a traditional algorithm of video independent reconstruction, the peak signal-to-noise ratio at a low sampling rate is improved and the reconstruction time is shortened.

Techniques and tools for reducing delay in video encoding and decoding by constraining delay due to reordering of video frames and by indicating constraints on frame reordering delay with one or more syntax elements accompanying encoded data for the video frame. For example, a real-time communication tool with a video encoder sets a syntax element indicating a constraint on a frame reordering delay consistent with an inter-frame correlation between frames of a video sequence, and then the The tool outputs this syntax element. A corresponding real-time communication tool having a video decoder receives the syntax element indicating a constraint on frame reordering delay, determines the constraint on frame reordering delay based on the syntax element, and uses the constraint on frame reordering delay to determine a reconstructed frame When to prepare for output (in terms of output order).

The invention discloses a face tampering video detection method, comprising: decoding the face video data into a group of continuous frame images, and intercepting the face area of ​​each frame image, and correspondingly saving it as a face picture according to the frame number; The feature extractor extracts each face picture and obtains the corresponding feature map; the feature maps of two consecutive frames are input to the inter-frame correlation classifier at the same time, and the inter-frame correlation classifier adopts the attention mechanism to combine the two frames. The feature maps are fused together for classification, and the classification result is the probability that the two input frames are tampered with. This method utilizes the information of the frame picture itself and the inter-frame relationship with its adjacent frames at the same time, which can achieve better results. At the same time, the detection is done automatically and can be applied to large-scale video platforms and social platforms.

The invention provides a target identification method based on quality evaluation. The target identification method based on quality evaluation includes the steps: constructing a target identificationmodel which includes a quality evaluation network, a feature extraction network, and a feature aggregation network, wherein the target identification model is used for extracting the target feature from a video so as to characterize the overall structural information and local information of the target; training the target identification model, and adjusting the parameters of the quality evaluation network and the feature extraction network during the training process so as to enable the target identification model to output the target feature according with the preset demand; and performingtarget identification on the video through the trained target identification model. Therefore, the target identification method based on quality evaluation solves the target identification problem caused by changeable appearance and irregular image quality in a video sequence, and adds the interframe correlation information in quality evaluation so as to obtain more effective target information toenable characterization of the target to be more accurate, thus improving the identification accuracy.