Abstract: Provided is a video streaming device that divides a video in which a plurality of viewing directions are defined into a plurality of divided data pieces and distributes each of the divided data pieces in a chronological order. The video streaming device includes: a prediction unit that refers to information indicating the viewing direction of a viewer for each of the divided data pieces with respect to a plurality of views of the video in the past, and predicts, for a terminal playing the video, the viewing direction of a user of the terminal in a first divided data piece that is undistributed; and a streaming unit that distributes the first divided data piece to the terminal by setting an area corresponding to the viewing direction predicted by the prediction unit to be in a relatively high image quality among selectable image qualities. Thereby, probability of viewing the video of a low image quality is decreased.

Abstract: An engagement estimation apparatus includes an acquisition unit configured to acquire, when stalling of a video delivered through a network occurs, a stalling position at occurrence of the stalling and a duration of the stalling, and an estimation unit configured to calculate an estimation value of an index for evaluation of engagement based on a property that the number of exited viewers increases as the stalling position is lengthened and as the duration increases. Thus, engagement can be estimated based on a parameter that can be observed in a terminal.

Abstract: A video quality estimation device for estimating a quality experienced by a user in a tile-based video distribution service in which a video is divided into tiles and distributed includes a video quality parameter extraction unit that extracts a first parameter representing a quality of a first tile and a second parameter representing qualities of one or more second tiles, from a received tile-based video; and a video quality estimation unit that estimates a quality of the tile-based video by using the first parameter and the second parameter.

Abstract: An engagement estimation apparatus includes an acquisition unit configured to acquire, for each measurement section after an instruction of a start of a view of an video delivered through a network, any of a parameter related to a coding quality of the video in the measurement section and a parameter related to a viewing state of the video in the measurement section, and an estimation unit configured to calculate an estimation value of an index for evaluation of engagement for each measurement section based on a parameter acquired by the acquisition unit in the measurement section. Thus, it is possible to estimate engagement based on parameters that can be observed in a terminal.

Abstract: This streaming design assistance method assists in the selection of an encoding condition for increasing the watching time in adaptive bitrate video streaming by causing a computer to execute: estimating a relationship between a watching time or an abandonment rate and an application quality index according to a mathematical model on the basis of an actual value of a watching time of each of a plurality of first sessions related to video streaming and an actual value of an application quality index of each of the sessions; estimating the application quality index of each of the sessions for each of a plurality of encoding conditions related to video streaming on the basis of the plurality of encoding conditions and an actual value of time-series throughput of each of a plurality of second sessions; and applying the application quality index estimated under each of the encoding conditions to the relationship to estimate an average watching time of the plurality of second sessions.

Abstract: An engagement estimation apparatus includes: an acquisition unit configured to acquire a value of a parameter affecting a quality of video streaming in a certain period; and a calculation unit configured to substitute the value of the parameter acquired by the acquisition unit in an equation representing a relation between the parameter indicative of the quality and engagement with the video streaming to calculate a value of an index indicative of the engagement, thereby enabling estimation of the engagement with the video streaming.

Abstract: A watching behavior estimation device includes an input unit to which a value of a first index indicating a playback state of a video distributed via a network is input, and a calculation unit configured to calculate, by applying the value which is input to the input unit to a function indicating a relationship between the first index, and a second index regarding a behavior of a viewer of the video, an estimated value of the second index, thereby making it possible to estimate the behavior of the viewer of the video distributed via the network.

Abstract: An audio-visual quality estimation device includes: an audio quality estimator to estimate audio quality for each unit time starting from a playback start time of an audio-visual content, based on a parameter affecting audio quality among parameters related to the content; a video quality estimator to estimate video quality for each unit time, based on a parameter affecting video quality among the parameters related to the content; a unit time quality estimator to unify the audio quality and video quality for each unit time, to estimate audio-visual quality for each unit time; an encoding quality estimator to unify the audio-visual quality for the unit times into one value, to estimate audio-visual encoding quality with respect to encoding degradation, considering temporal quality fluctuation; and an audio-visual quality estimator to estimate the audio-visual quality perceived by a viewer after an end of the content, based on the audio-visual encoding quality.

Abstract: An audio-visual quality estimation device includes: an audio quality estimator to estimate audio quality for each unit time starting from a playback start time of an audio-visual content, based on a parameter affecting audio quality among parameters related to the content; a video quality estimator to estimate video quality for each unit time, based on a parameter affecting video quality among the parameters related to the content; a unit time quality estimator to unify the audio quality and video quality for each unit time, to estimate audio-visual quality for each unit time; an encoding quality estimator to unify the audio-visual quality for the unit times into one value, to estimate audio-visual encoding quality with respect to encoding degradation, considering temporal quality fluctuation; and an audio-visual quality estimator to estimate the audio-visual quality perceived by a viewer after an end of the content, based on the audio-visual encoding quality.

Abstract: A video quality evaluation apparatus for evaluating a video quality that a user experiences for a service in which a 3D video is used, the video quality evaluation apparatus including: a 2D video quality derivation unit configured to derive, from input 3D video data, a left eye video quality that is a quality of a left eye video that is included in the 3D video data and a right eye video quality that is a quality of a right eye video that is included in the 3D video data; and a 3D video quality derivation unit configured to derive a quality of the 3D video from the left eye video quality and the right eye video quality.

Abstract: This invention provides a video quality estimation apparatus (1) including a packet analysis unit (10) that derives the bit rate of an encoded video packet contained in an input packet, and the bit amount of the encoded video packet for each encoded video frame type, a video subset frame characteristic estimation unit (11) that derives the frame characteristic of each video frame type from the bit rate derived by the packet analysis unit (10), and an encoding quality estimation unit (12) that derives, based on the bit rate and the bit amount of each video frame type, a video quality value quantitatively representing the quality of encoded video data that is affected by encoding degradation. The video quality estimation apparatus performs more accurate video quality estimation by taking account of the bit amount of each video frame type.

Abstract: A video quality evaluation apparatus for evaluating a video quality that a user experiences for a service in which a 3D video is used, the video quality evaluation apparatus including: a 2D video quality derivation unit configured to derive, from input 3D video data, a left eye video quality that is a quality of a left eye video that is included in the 3D video data and a right eye video quality that is a quality of a right eye video that is included in the 3D video data; and a 3D video quality derivation unit configured to derive a quality of the 3D video from the left eye video quality and the right eye video quality.

Abstract: A multi-modal quality estimation unit (11) estimates a multi-modal quality value (23A) on the basis of an audio quality evaluation value (21A) and a video quality evaluation value (21). In addition, a delay quality degradation amount estimation unit (12) estimates a delay quality degradation amount (23B) on the basis of an audio delay time (22A) and a video delay time (22B). A video communication quality estimation unit (13) estimates a video communication quality value (24) on the basis of a multi-modal quality value (23A) and a delay quality degradation amount (23B).

Abstract: A packet loss frequency calculation unit (102) which counts, from an extracted packet loss pattern, packet losses generated in a predetermined interval representing the interval of a plurality of continuous IP packets as a packet loss of one time, thereby calculating the value as a packet loss frequency. The packet loss frequency calculation unit (102) also calculates a burst packet loss length representing the number of continuously lost packets from the packet loss pattern. An average burst packet loss length within a quality estimation interval is calculated from the burst packet loss length. A packet loss variation index calculation unit (106) derives a packet loss variation index from the average burst packet loss length. On the other hand, an encoding quality calculation unit (103) calculates an encoded video quality value based on the extracted encoding bit rate and frame rate.

Abstract: This invention provides a video quality estimation apparatus (1) including a packet analysis unit (10) that derives the bit rate of an encoded video packet contained in an input packet, and the bit amount of the encoded video packet for each encoded video frame type, a video subset frame characteristic estimation unit (11) that derives the frame characteristic of each video frame type from the bit rate derived by the packet analysis unit (10), and an encoding quality estimation unit (12) that derives, based on the bit rate and the bit amount of each video frame type, a video quality value quantitatively representing the quality of encoded video data that is affected by encoding degradation. The video quality estimation apparatus performs more accurate video quality estimation by taking account of the bit amount of each video frame type.

Abstract: In estimating subjective video quality corresponding to main parameters which are input as an input frame rate representing the number of frames per unit time, an input coding bit rate representing the number of coding bits per unit time, and an input packet loss rate representing a packet loss occurrence probability of an audiovisual medium, a degradation model specifying unit specifies a degradation model representing the relationship between the packet loss rate and the degradation in reference subjective video quality on the basis of the input frame rate and input coding bit rate. A desired subjective video quality estimation value is calculated by correcting the reference subjective video quality on the basis of a video quality degradation ratio corresponding to the input packet loss rate calculated by using the degradation model.

Abstract: In estimating subjective video quality corresponding to main parameters (121/221) which are input as an input coding bit rate (121B/221B) representing the number of coding bit rates per unit time and an input frame rate (121A/221A) representing the number of frames per unit time of an audiovisual medium, an estimation model specifying unit specifies, on the basis of the input coding bit rate (121B/input frame rate (221A)), an estimation model (122/222) representing the relationship between subjective video quality and the frame rate (/coding bit rate) of the audiovisual medium. Subjective video quality corresponding to the input frame rate (121A/input coding bit rate 221B) is estimated by using the specified estimation model (122/222) and output as an estimation value (123/223).

Abstract: A motion vector or DCT coefficient which exists in the bit string of an encoded video and serves as a parameter representing the difference between scenes, or encoding control information or pixel information obtained by partially decoding the bit string of the encoded video is used for video quality objective assessment. It is consequently possible to save the amount of pixel information decoding processing that requires an enormous amount of calculation as compared to video quality objective assessment apparatus using pixel information obtained by decoding the bit string of an entire video. This allows to perform video quality objective assessment in a short time using an inexpensive computer.

Abstract: A bit string of a video encoded using motion-compensated inter-frame prediction and DCT and, more particularly, H.264 is received. A quantization parameter included in the received bit string is extracted, and its statistic is calculated. The subjective quality of the video is estimated based on the minimum value of the quantization parameter.

Abstract: A packet loss frequency calculation unit (102) which counts, from an extracted packet loss pattern, packet losses generated in a predetermined interval representing the interval of a plurality of continuous IP packets as a packet loss of one time, thereby calculating the value as a packet loss frequency. The packet loss frequency calculation unit (102) also calculates a burst packet loss length representing the number of continuously lost packets from the packet loss pattern. An average burst packet loss length within a quality estimation interval is calculated from the burst packet loss length. A packet loss variation index calculation unit (106) derives a packet loss variation index from the average burst packet loss length. On the other hand, an encoding quality calculation unit (103) calculates an encoded video quality value based on the extracted encoding bit rate and frame rate.