In various embodiments, a prediction application computes a quality score for re-constructed visual content that is derived from visual content. The prediction application generates a frame difference matrix based on two frames included in the re-constructed video content. The prediction application then generates a first entropy matrix based on the frame difference matrix and a first scale. Subsequently, the prediction application computes a first value for a first temporal feature based on the first entropy matrix and a second entropy matrix associated with both the visual content and the first scale. The prediction application computes a quality score for the re-constructed video content based on the first value, a second value for a second temporal feature associated with a second scale, and a machine learning model that is trained using subjective quality scores. The quality score indicates a level of visual quality associated with streamed video content.

A method, comprises monitoring a encoding process of a source video file performed by an encoder; obtaining an encoding decision parameter used to encode a picture of the source video file during the encoding process; comparing the encoding decision parameter to a threshold; based on the step of comparing, identifying the picture as a candidate picture for a visual defect or coding error; and storing a timestamp of the candidate picture.

The present technology relates to a signal processing device and method, and a program that enable easier and more accurate failure detection. The signal processing device includes: an addition unit that adds test data for failure detection to valid data on which predetermined processing is to be performed, two or more samples processed in parallel in different paths having a same sample value in the test data; and a signal processing unit that performs the predetermined processing on the valid data and the test data that has been added to the valid data by a plurality of the paths. The present technology can be applied to in-car cameras.

The present disclosure provides a video jitter detection method and an apparatus. The video jitter detection method includes: acquiring a video; inputting the video into a detection model to obtain an evaluation value of the video, where the evaluation value is used to indicate a degree of jitter of the video; where the detection model is a model obtained by training using video samples in a video sample set as inputs and evaluation values of the video samples in the video sample set as outputs. By inputting the video to be detected into the detection model, the evaluation value of the video can be acquired through the detection model, thereby whether the video is jittery is determined, which realizes the video jitter detection end-to-end, and improves the detection accuracy and robustness of video jitter.

Techniques are described for expanding and/or improving the Advanced Television Systems Committee (ATSC) 3.0 television protocol in robustly delivering the next generation broadcast television services. In a boundary region between first and second broadcast stations in which a receiver can pick up signals from both stations, a primary tuner receiving signals from plural antennae presents a demanded service while a secondary tuner uses a single antenna to scan for duplicate transmissions of the service, and if one is found, the version with the better quality metrics may be presented.

An method for determining a video coding test sequence, an electronic device, and a computer readable storage medium are provided. The method includes: determining a candidate video set including multiple candidate videos corresponding to a target service requirement; classifying the candidate videos by content categories to obtain a target distribution of content categories; clustering the candidate videos by values of a preset coding complexity to obtain multiple video classes; selecting from each of the video classes respectively a target class-representative video such that an actual distribution of content categories is consistent with the target distribution of content categories; and constructing a target video coding test sequence based on the target class-representative videos.

A controller for calibrating a videoconferencing system is disclosed. The system includes a first codec connected to a second codec through a videoconferencing connection. The controller includes an output in communication with the first codec for controlling the first codec to transmit a videoconferencing signal to the second codec through the videoconferencing connection, and an input for receiving a calibration adjustment value from another controller over a network, where the other controller is in communication with the second codec. The controller is configured to adjust a signal level setting of the first codec using a level adjustment command of the first codec, and the level adjustment command is determined according to the calibration adjustment value transmitted by the other controller.

A method and a system for assessing quality of multimedia content are disclosed. In an embodiment, the method may include receiving a multimedia content which may be captured from a media device. The method may further include generating a plurality of frames from the multimedia content, based on an attribute associated with the multimedia content. The method may further include determining, for each frame, a set of parameter quality scores corresponding to a set of quality parameters, and calculating an overall quality score for the multimedia content based on the set of parameter quality scores for each of the plurality of frames associated with the multimedia content.

An apparatus comprising (1) a conoscope configured to receive an image emitted by a display device through a corrective lens, (2) a variable compensation element coupled to the conoscope, wherein the variable compensation element is capable of selectively modifying the image emitted by the display device to compensate for an optical effect imparted by the corrective lens on the image, and (3) a controller coupled to the variable compensation element, wherein the controller (1) receives a compensation parameter representative of the optical effect imparted by the corrective lens on the image, (2) selects, based at least in part on the compensation parameter, a feature of the variable compensation element that compensates for the optical effect, and (3) causing the feature of the variable compensation element to be applied to the image. Various other apparatuses, systems, and methods are also disclosed.

Provided is a method for detecting live streaming jitter, a device, and a medium. An implementation is: calculating, for a live stream transmitted by an edge content delivery network (CDN) node in a CDN, quality information of the live stream based on a transmission frame rate and a viewer count of the live stream; calculating quality information of the edge CDN node based on the quality information of the live stream; and determining, based on the quality information of the edge CDN node, whether jitter occurs at the edge CDN node.