A method for encoding including executing game logic built on a game engine of a video game at a cloud gaming server to generate video frames. The method including executing scene change logic to predict a scene change in the video frames based on game state collected during execution of the game logic. The method including identifying a range of video frames that is predicted to include the scene change. The method including generating a scene change hint using the scene change logic, wherein the scene change hint identifies the range of video frames, wherein the range of video frames includes a first video frame. The method including delivering the first video frame to an encoder. The method including sending the scene change hint from the scene change logic to the encoder. The method including encoding the first video frame as an I-frame based on the scene change hint.

Approaches to selection of motion vector (“MV”) precision during video encoding are presented. These approaches can facilitate compression that is effective in terms of rate-distortion performance and/or computational efficiency. For example, a video encoder determines an MV precision for a unit of video from among multiple MV precisions, which include one or more fractional-sample MV precisions and integer-sample MV precision. The video encoder can identify a set of MV values having a fractional-sample MV precision, then select the MV precision for the unit based at least in part on prevalence of MV values (within the set) having a fractional part of zero. Or, the video encoder can perform rate-distortion analysis, where the rate-distortion analysis is biased towards the integer-sample MV precision. Or, the video encoder can collect information about the video and select the MV precision for the unit based at least in part on the collected information.

Approaches to selection of motion vector (“MV”) precision during video encoding are presented. These approaches can facilitate compression that is effective in terms of rate-distortion performance and/or computational efficiency. For example, a video encoder determines an MV precision for a unit of video from among multiple MV precisions, which include one or more fractional-sample MV precisions and integer-sample MV precision. The video encoder can identify a set of MV values having a fractional-sample MV precision, then select the MV precision for the unit based at least in part on prevalence of MV values (within the set) having a fractional part of zero. Or, the video encoder can perform rate-distortion analysis, where the rate-distortion analysis is biased towards the integer-sample MV precision. Or, the video encoder can collect information about the video and select the MV precision for the unit based at least in part on the collected information.

Methods and devices are provided for encoding a video stream which comprise encoding a plurality of frames of video acquired from different points of view, generating statistical values for the frames of video determined from values of pixels of the frames, generating, for each of the plurality of frames, a perceptual hash value based on statistical values of the frame and encoding a current frame comprising video acquired from a corresponding one of the different points of view using a previously encoded reference frame based on a similarity of perceptual hashes of the current frame and the previously encoded reference frame.

Methods and devices are provided for encoding a video stream which comprise encoding a plurality of frames of video acquired from different points of view, generating statistical values for the frames of video determined from values of pixels of the frames, generating, for each of the plurality of frames, a perceptual hash value based on statistical values of the frame and encoding a current frame comprising video acquired from a corresponding one of the different points of view using a previously encoded reference frame based on a similarity of perceptual hashes of the current frame and the previously encoded reference frame.

In the video processing device, the video acquisition means acquires a material video. The audience scene extraction means extracts an audience scene showing an audience from the material video. The important scene extraction means extracts an important scene from the material video. The association means associates the audience scene with the important scene. The generation means generates a digest video including the important scene and the audience scene associated with the important scene.

In the video processing device, the video acquisition means acquires a material video. The audience scene extraction means extracts an audience scene showing an audience from the material video. The important scene extraction means extracts an important scene from the material video. The association means associates the audience scene with the important scene. The generation means generates a digest video including the important scene and the audience scene associated with the important scene.

A method for enhancing at least a section of lower-quality visual data using a hierarchical algorithm, the method comprising receiving at least a plurality of neighbouring sections of lower-quality visual data. A plurality of input sections from the received plurality of neighbouring sections of lower quality visual data are selected and features are extracted from those plurality of input sections of lower-quality visual data. A target section based on the extracted features from the plurality of input sections of lower-quality visual data is then enhanced.

There is provided an image archiving method for use with a writing target, comprising the steps of receiving a series of captured images of the writing target, detecting difference between first and second candidate received images separated by a predetermined period of time, where additive differences are indicative of writing and subtractive differences are indicative of erasure; upon detecting subtractive difference, temporarily retaining a last candidate image captured prior to the detection, and detecting whether the subtractive difference relative to the retained image exceeds a subtraction threshold amount; and if so, then storing the retained image.

An information processing apparatus includes a control unit that performs first control processing of deciding an analysis engine for scene detection from among a plurality of analysis engines on the basis of scene detection information for scene detection with respect to an input video, and second control processing of deciding an analysis engine for obtaining second result information related to the scene from among a plurality of analysis engines, on the basis of scene-related information regarding a scene obtained as first result information by the analysis engine decided in the first control processing.