3 results about "Video quality degradation" patented technology

The invention provides a video quality analysis method, device and equipment and a medium, and belongs to the technical field of video quality evaluation. The method comprises the following steps: acquiring original video data, and generating degraded video data with noise intensity, definition score and compression damage degree three-dimensional real labels through composite degradation processing; training a multi-task deep joint prediction network by using the data set; and inputting a real world degraded video to be analyzed into the trained network model, and outputting a corresponding noise intensity predicted value, a definition score predicted value and a compression damage degree predicted value. Compared with the prior art, the method has the advantages that high-fidelity simulation and automatic accurate evaluation of video multi-dimensional quality degradation factors can be realized, and the accuracy of a noise intensity prediction value, a definition score prediction value and a compression damage degree prediction value is improved; the method can be used for video coding and decoding optimization, network transmission quality control, video enhancement processing and other scenes.

The application discloses a railway video quality self-diagnosis system based on multi-domain self-calibration, relates to the technical field of railway video monitoring, and specifically comprises the following modules: a data acquisition module, a multi-domain extraction module, a cross-domain diagnosis module, a self-calibration execution module and a closed-loop feedback module; visible light video frame sequences of a railway perimeter are collected in real time; feature extraction is respectively performed on the video frames in the time-space domain, the frequency domain and the semantic domain; multi-domain features are fused to generate comprehensive quality diagnosis results; calibration parameters are dynamically generated and applied according to the diagnosis results to perform adaptive optimization of the video quality; the video after calibration is verified for effects, and historical high-quality reference templates are updated; the video quality degradation condition can be comprehensively and finely perceived, and targeted calibration strategies are dynamically generated according to the diagnosis results, so that false detection and missed detection caused by video blur, noise, geometric deviation and semantic loss are effectively reduced, high-quality input data can be provided for applications such as foreign matter intrusion detection and boundary intrusion recognition.

The application provides a camera patrol video quality diagnosis and optimization method and system and a storage medium. The method comprises the following steps: acquiring original video stream collected by a camera, device metadata associated with the camera, and network performance data, analyzing the original video stream to extract video content quality features; constructing a heterogeneous node set based on the video content quality features, the device metadata, and the network performance data, and constructing a dynamic multi-modal spatio-temporal feature graph with edges representing the bearing or spatio-temporal correlation between nodes as a heterogeneous edge set; inputting the dynamic multi-modal spatio-temporal feature graph into a spatio-temporal graph neural network to capture the propagation path of faults in the heterogeneous node set and output the abnormal probability of each node; taking the abnormal probability and the propagation path as a query condition to match and cooperatively reason in a pre-constructed knowledge graph to determine the root cause and the corresponding evidence chain causing the video quality to decrease; and matching an optimization strategy based on the root cause. The application improves the reliability and operation and maintenance efficiency of video monitoring.