A method, a system, and an apparatus for evaluating video quality are disclosed to improve accuracy of the evaluation. The method includes: obtaining information about a transmitted video; resolving the information about the transmitted video to obtain video frame parameters, where the video frame parameters include a compression distortion parameter and/or a video quality distortion parameter with packet loss; and calculating a video frame quality parameter according to the video frame parameters. An apparatus and a system for evaluating video quality are provided. The embodiments of the present invention improve accuracy of video quality evaluation without reference.

The invention provides a method and apparatus for detecting a gradual transition picture in a bitstream. The method comprises: accessing a bitstream including encoded pictures; and determining a gradual transition picture in the bitstream using information from the bitstream without decoding the bitstream to derive pixel information.

Because neighboring frames may affect how a current frame is perceived, we examine different neighborhoods of the current frame and select a neighborhood that impacts the perceived temporal distortion (i.e., when frames are viewed continuously) of the current frame most significantly. Based on spatial distortion (i.e., when a frame is viewed independently of other frames in a video sequence) of frames in the selected neighborhood, we can estimate initial temporal distortion. To refine the initial temporal distortion, we also consider the distribution of distortion in the selected neighborhood, for example, the distance between the current frame and a closest frame with large distortion, or whether distortion occurs in consecutive frames.

In various embodiments, a quality inference application estimates the perceived quality of reconstructed videos. The quality inference application computes a first feature value for a first feature included in a feature vector based on a color component associated with a reconstructed video. The quality inference application also computes a second feature value for a second feature included in the feature vector based on a brightness component associated with the reconstructed video. Subsequently, the quality inference application computes a perceptual quality score based on the first feature value and the second feature value. The perceptual quality score indicates a level of visual quality associated with at least one frame included in the reconstructed video.

The present application relates to set top boxes and relates to the inclusion of a diagnostic function in the set top box which may be activated remotely or respond internally to the detection of faults or changes in status. The diagnostic function may emulate key presses from an infrared remote control to perform a test.

A method and a device for assessing video encoding quality. The method includes: acquiring a quantization parameter of a slice of a video frame and a quantity of bytes per pixel of the slice of the video frame of the video stream; determining complexity of content of the video according to the quantity of bytes per pixel of the slice of the video frame of the video stream; and predicting the video encoding quality according to the complexity of content of the video and the quantization parameter of the video. In the present invention, the complexity of content of the video is also considered in predicting the video encoding quality. Therefore, encoding quality predicted by a model that is obtained by considering the complexity of content of the video better satisfies subjective feelings of human eyes, thereby improving accuracy of prediction.

Disclosed are a system and method for performing distortion correction and calibration using a pattern projected by a projector. The system for performing distortion correction and calibration includes a projector that projects a pattern, at least one camera that generates a photographed pattern image by photographing an image onto which the pattern is projected, and an image processing device that calculates a calibration parameter by comparing an original pattern image projected by the projector and the photographed pattern image. Thus, it is possible to obtain an accurate depth image by easily utilizing an image for the pattern projected by the projector. In addition, when obtaining the depth image, the calibration parameter for correcting image distortion according to camera lens and a calibration state of cameras may be efficiently obtained using the pattern projected by the projector.

A system for remotely monitoring and controlling one or more electronic displays containing several hardware components. The components may electronically communicate with a network connection which can be used to establish communication with a local area network and/or the internet. A personal computing device can be used to run a user interface which allows the user to access a wealth of information from the electronic display as well as change controlling software, operating parameters, and check for downtime incidents or failures. Various sensors and measurement devices can be installed within the display to provide the information which may be stored locally or stored remotely for real-time access or on-demand access.

A marker generating method is provided for facilitating the finding of positions which correspond to one another among a plurality of images associated with a video signal. A position within an image (800) associated with a video signal is selected, with a cursor (802, 804) to display a marker (812, 822-826) at a position corresponding to the selected position, in a different image (810, 820) associated with the video signal.

A macroblock in a video sequence may be undecodable because the corresponding compressed data is lost or the syntax is out of synchronization. An undecodable macroblock may be concealed using error concealment technique. The level of initial visible artifacts caused by undecodable macroblocks may be estimated as a function of motion magnitude, error concealment distance, and/or residual energy. The initial visible artifacts may propagate spatially or temporally to other macroblocks through prediction. Considering both initial visible artifacts and propagated artifacts, levels of overall artifacts may be estimated for individual macroblocks. The visual quality for the video sequence can then be estimated by pooling the macroblock level artifact levels.