A video service quality assessment method and apparatus, where a monitoring device is configured to: obtain an identifier of a to-be-monitored channel, an identifier of to-be-monitored user equipment, and configuration information of a video service transmission system; obtain a multicast video stream of the to-be-monitored channel based on the identifier of the to-be-monitored channel; obtain a retransmitted video stream based on the identifier of the to-be-monitored channel, the identifier of the to-be-monitored user equipment, and the configuration information of the video service transmission system; determine a to-be-assessed video stream based on the multicast video stream and the retransmitted video stream; parse the to-be-assessed video stream; and obtain an assessment result based on a parsing result and the configuration information of the video service transmission system.

In various embodiments, an encoding metric comparison application computes a first set of quality scores associated with a test encoding configuration based on a set of bootstrap quality models. Each bootstrap quality model is trained based on a different subset of a training database. The encoding metric comparison application computes a second set of quality scores associated with a reference encoding configuration based on the set of bootstrap quality models. Subsequently, the encoding metric comparison application generates a distribution of bootstrap values for an encoding comparison metric based on the first set of quality scores and the second set of quality scores. The distribution quantifies an accuracy of a baseline value for the encoding comparison metric generated by a baseline quality model.

Various techniques include detecting noise in a network, identifying the type of noise in the network, localizing noise in the network, determining noise scores for network devices, and/or determining likelihoods that particular devices are causing noise and/or are in proximity of a point of entry of noise into the network.

A game streaming system encodes a raw frame to generate an encoded frame for a game stream including a plurality of frames for display. The system identifies a first encoding artifact based on a first difference between the encoded frame and the raw frame, and applies an overlay to the encoded frame. The overlay includes a first visual indicator indicating the first encoding artifact.

Systems, methods, and devices relating to video stream signal analysis are described herein. In a method, a first video stream configured with a first plurality of signals associated with inserting content may be determined. The first plurality of signals may be extracted from the first video stream and temporally compressed. A second video stream may be configured with the compressed first plurality of signals. Based on whether the compressed first plurality of signals caused any errors in processing the second video stream, it may be determined whether the uncompressed first plurality of signals are expected to cause any errors in processing the first video stream configured with the uncompressed first plurality of signals.

Methods and systems for monitoring a service provided over a packet-switched network, such as an Internet Protocol television (IPTV) service, an Internet access service, or a voice-over-Internet-Protocol (VoIP) telephony service. Various parameters related to the service (e.g., parameters indicative of packet loss, packet corruption, or other packet error) are determined and used to assess various aspects of the service and/or network over which the service is delivered, including a quality of experience (QoE) of subscribers.

A testing system and application performs validation testing on a media services delivery system by generating test transactions and validating test results at a plurality of support systems updated by the test transactions in a test environment. Support systems are independent systems that may be geographically and network distant, thus are cumbersome to access for validating corresponding updates based on a test transaction. The test system is accessible via an Internet or network portal for accessing an application that generates a test transaction, invokes a system under test for implementing the test transaction, and validates the results of the support system updates with known values for successful test completion. The test system automates the identification, retrieval and comparison of test generated values with known values corresponding to a successful transaction, and is operable to perform a suite of tests in succession from a set of predetermined test transactions and corresponding known values.

A method includes receiving, by a system-on-a-chip (SoC) from a camera mounted on a vehicle, a first image and transmitting, by the SoC to a display circuit over an interface cable, the first image. The method also includes receiving, by the SoC from the display circuit, a feedback signature corresponding to the first image. Additionally, the method includes detecting, by the SoC, an error, in response to determining that the feedback signature does not match the transmission-side signature and transmitting, by the SoC to the display circuit, a second image, in response to determining that the feedback signature matches the transmission-side signature.

In a camera calibration apparatus (10), an acquisition unit (11) acquires a first normal vector in an image plane and a second normal vector in the image plane respectively corresponding to a first normal vector in a world coordinate space and a second normal vector in the world coordinate space which are normal vectors with respect to a reference plane in the world coordinate space and have the same length. A projective depth calculation unit (12) calculates a projective depth vector having, as vector elements, four projective depths respectively corresponding to a start point and an end point of the first normal vector in the image plane and a start point and a end point of the second normal vector in the image plane.

The disclosed computer-implemented method may include receiving original media content, transcoding the original media content into a plurality of encoded media files, determining an adaptive bit rate for providing a one of the plurality of encoded media files to a computing device, delivering the encoded media file to the computing device at the adaptive bit rate for viewing on a display device of the computing device, and measuring a quality of the displayed encoded media file based on an overall mean opinion score associated with the delivered encoded media file. The overall mean opinion score may be based on a measured playback quality associated with the encoded media file and a measured upload quality associated with the original media content. Various other methods, systems, and computer-readable media are also disclosed.