WO2013177910A1 - 一种媒体质量的评估方法及装置 - Google Patents
一种媒体质量的评估方法及装置 Download PDFInfo
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- WO2013177910A1 WO2013177910A1 PCT/CN2012/085710 CN2012085710W WO2013177910A1 WO 2013177910 A1 WO2013177910 A1 WO 2013177910A1 CN 2012085710 W CN2012085710 W CN 2012085710W WO 2013177910 A1 WO2013177910 A1 WO 2013177910A1
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- 238000000034 method Methods 0.000 title claims abstract description 46
- 230000003993 interaction Effects 0.000 claims abstract description 42
- 230000000694 effects Effects 0.000 claims abstract description 15
- 238000013441 quality evaluation Methods 0.000 abstract description 20
- 238000001303 quality assessment method Methods 0.000 description 12
- 238000004364 calculation method Methods 0.000 description 11
- 230000008569 process Effects 0.000 description 10
- 230000006870 function Effects 0.000 description 3
- 229940038850 rebif Drugs 0.000 description 3
- 101001073212 Arabidopsis thaliana Peroxidase 33 Proteins 0.000 description 2
- 101001123325 Homo sapiens Peroxisome proliferator-activated receptor gamma coactivator 1-beta Proteins 0.000 description 2
- 108010005716 Interferon beta-1a Proteins 0.000 description 2
- 102100028961 Peroxisome proliferator-activated receptor gamma coactivator 1-beta Human genes 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 230000006978 adaptation Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000006835 compression Effects 0.000 description 1
- 238000007906 compression Methods 0.000 description 1
- 238000011217 control strategy Methods 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
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- 230000003287 optical effect Effects 0.000 description 1
- 230000008447 perception Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Classifications
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N17/00—Diagnosis, testing or measuring for television systems or their details
- H04N17/004—Diagnosis, testing or measuring for television systems or their details for digital television systems
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N17/00—Diagnosis, testing or measuring for television systems or their details
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N17/00—Diagnosis, testing or measuring for television systems or their details
- H04N17/02—Diagnosis, testing or measuring for television systems or their details for colour television signals
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
- H04N19/85—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using pre-processing or post-processing specially adapted for video compression
- H04N19/89—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using pre-processing or post-processing specially adapted for video compression involving methods or arrangements for detection of transmission errors at the decoder
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/20—Servers specifically adapted for the distribution of content, e.g. VOD servers; Operations thereof
- H04N21/23—Processing of content or additional data; Elementary server operations; Server middleware
- H04N21/234—Processing of video elementary streams, e.g. splicing of video streams or manipulating encoded video stream scene graphs
- H04N21/23418—Processing of video elementary streams, e.g. splicing of video streams or manipulating encoded video stream scene graphs involving operations for analysing video streams, e.g. detecting features or characteristics
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
- H04N21/43—Processing of content or additional data, e.g. demultiplexing additional data from a digital video stream; Elementary client operations, e.g. monitoring of home network or synchronising decoder's clock; Client middleware
- H04N21/44—Processing of video elementary streams, e.g. splicing a video clip retrieved from local storage with an incoming video stream or rendering scenes according to encoded video stream scene graphs
- H04N21/44008—Processing of video elementary streams, e.g. splicing a video clip retrieved from local storage with an incoming video stream or rendering scenes according to encoded video stream scene graphs involving operations for analysing video streams, e.g. detecting features or characteristics in the video stream
Definitions
- the invention belongs to the technical field of communications, and in particular relates to a method and a device for evaluating media quality. Background technique
- Video quality assessment is an essential technology in video applications. Video quality is affected by many complex factors, including: the quality of service of the transport channel (such as bandwidth, packet loss, delay, jitter, etc.), and the adaptation of the video codec parameters to the transport channel (eg, coding, video resolution). Rate, video frame rate, error-resistant strength, whether the codec side buffer control strategy is appropriate, etc.). In addition to video loss due to loss of video data, such as channel loss, coding, etc., video delay or jitter caused by video delay and jitter can seriously affect the quality of the video.
- the existing video quality assessment model takes into account the impact of coding quality, the effects of video stalls, and the effects of network packet loss:
- the coding quality takes into account the effects of the code stream and the encoding format:
- C. , c ⁇ p /L is a constant, different encoding formats can have different values.
- the network packet loss quality is calculated by using the packet loss rate. First, the average packet loss rate in the sliding window is calculated.
- PLR p PLR The default maximum packet loss rate, PLR p PLR, is considered to be the worst quality if the packet loss rate in the sliding window is greater than the PLR. If the packet loss rate is less than the PLR, the packet loss is considered to have no effect on the video quality:
- the quality of the lost packet over a period of time is:
- the effect of video pauses takes into account the effects of video pauses, re-buffering durations, and initial buffer duration over a period of time.
- the model is as follows:
- the purpose of the embodiments of the present invention is to provide a method for evaluating media quality, so as to solve the problem that the interaction between the multiple pause events and the impact of the media content in the video quality assessment in the prior art is not considered.
- the impact of the initial quality of the media leads to problems that do not match the subjective perceptions of existing video quality assessments.
- the embodiment of the present invention is implemented by the method for evaluating the quality of the media, wherein the method includes:
- the parameter of the pause event distortion quality includes at least one of the following: the number of pause events, the pause event duration, the multiple pause event interaction influence parameters, and the media initial quality. And a media content complexity description factor.
- a final quality of the media is determined based on the calculated media quality of each of the score segments.
- the embodiment of the present invention further provides an apparatus for evaluating media quality, the apparatus comprising: an obtaining unit, configured to obtain a media reference quality and a distortion quality of a pause event; and a determining unit, configured to obtain a media reference quality according to the acquiring unit And the quality of the distortion of the pause event determines the final quality of the media;
- the parameters of the stall event distortion quality include at least one of the following: the number of pause events, the duration of the pause event, the interaction impact parameter of the multiple pause events, the media initial quality, and the media content complexity description factor.
- a device for evaluating media quality comprising:
- a scoring segment dividing unit configured to divide the media file to be evaluated into a plurality of scoring segments; a reference quality and a staging event distortion quality, wherein the parameter of the scrambled event distortion quality of the scoring segment includes at least one of the following: a number of pause events, a pause event Duration, multiple pause events, interaction parameters, media initial quality, and media content complexity description factors; a determining unit, configured to calculate the media of each of the score segments according to the calculating unit Quality determines the final quality of the media.
- the embodiment of the present invention considers the influence of multiple pause event interaction influence parameters, media initial quality, and media content complexity description factors on media quality when calculating media quality, thereby making media quality
- the assessment results are more accurate and more consistent with people's subjective feelings.
- FIG. 1 is a flowchart of implementing a media quality evaluation method according to Embodiment 1 of the present invention
- FIG. 2 is a pause interval histogram according to Embodiment 1 of the present invention
- FIG. 3 is a flowchart of an implementation of a media quality evaluation method according to Embodiment 2 of the present invention
- FIG. 4 is a flowchart of an implementation of a media quality evaluation method according to Embodiment 3 of the present invention
- FIG. 6 is a flowchart of an implementation of a media quality evaluation method according to Embodiment 5 of the present invention
- FIG. 7 is a structural diagram of a media quality evaluation apparatus according to Embodiment 6 of the present invention
- Figure 8 is a block diagram showing the structure of a media quality evaluation apparatus according to a seventh embodiment of the present invention.
- the media reference quality is the distortion caused by media coding compression, which is the basic quality of encoding different media streams to different code rates under different coding types.
- Packet loss is the damage of media frames (such as video frames and/or audio frames) caused by delay packets caused by loss or jitter of media stream packets transmitted in the network channel. Errors due to frame damage. Distortion and error propagation distortion, the degree of distortion and the magnitude of the distortion value depend on the underlying quality of the encoding.
- the media content complexity description factor represents a description of the media content complexity of the media content in time, space or integrated time and space, for example: the faster the video sequence or the more detailed or richer the video sequence The video content complexity description factor is larger.
- Stall event For a video sequence, the effect of the pause event is represented by repeatedly displaying the last displayed image or a continuous still image. For audio sequences, the effect of a pause event is manifested by repeating the audio of one frame/segment before playback or without sound. For audio and video sequences, the effect of the stall event is a combination of the two.
- Embodiments of the present invention are applicable to video pauses, audio pauses, and evaluation of audio and video pause quality.
- the media in the embodiment of the present invention includes video, audio or audio and video.
- pause events and packet loss distortion can occur in the media simultaneously or separately.
- the following description will be made by way of specific embodiments.
- Embodiment 1 is a diagrammatic representation of Embodiment 1:
- FIG. 1 is a flowchart showing an implementation process of a media quality assessment method according to Embodiment 1 of the present invention. The process is detailed as follows:
- step S101 the media reference quality and the pause event distortion quality are obtained.
- the media reference quality can be obtained by using the prior art, and details are not described herein again.
- the parameters of the stall quality of the pause event include, but are not limited to, at least one of the following: the number of pause events, the pause event duration, the multiple pause event interaction influence parameters, the media initial quality, and the media content complexity description factor.
- the parameters of the stalling event quality include, but are not limited to, at least one of the following: multiple pause event interaction influence parameters, media initial quality, and media content complexity description factor.
- the parameter of the quality of the pause event distortion includes a media initial quality, a number of pause events, and a pause event duration
- Q rebuf func (Video _ Quality, Rebuf _ Num, Rebuf _ Len).
- the parameters of the quality of the pause event distortion include media initial quality, number of pause events, pause event duration, and multiple pause event interaction influence parameters
- Q rebuf func ⁇ Video _ Quality, Rebuf _ Num, Rebuf _ Len, MultiRebuf _ Factor ⁇ .
- Q rebuf indicates the distortion quality of the pause event
- / indicates the initial quality of the media
- Reb /_N indicates the number of pause events
- Reb /_Le « indicates the duration of the pause event
- M to'Reb /_ 3 ⁇ 4ctor indicates the interaction parameters of multiple pause events .
- the specific calculation formula can be: ⁇ W Len t
- Rebuf - Len , where w represents the occurrence of a pause event within the preset time
- the total number of times, L indicates the duration of the first pause event in the preset time
- ⁇ indicates the weighting coefficient of the first pause event (can be an equal constant, or the weight set according to the pause duration, the longer the pause time , the greater the weight, the smaller the anyway)
- Reb /_L represents the weighted average duration of the pause event within the preset time
- the duration of the pause event is a ratio of the total duration of the pause event to the preset time in the preset time period, and the specific calculation formula may be:
- Rebuf _ Len ⁇ -, where "represents the total number of pauses in the preset time period
- the number, L represents the duration of the first pause event in the preset time
- 7 me represents the preset time
- Rebuf_Len represents the ratio of the total duration of the pause event in the preset time period to the preset time; Or the duration of the pause event is the total duration of the pause time in the preset time period, and the specific calculation formula may be:
- Rebuf _ Len j Le ⁇ , where "represents the total number of pause events in the preset time period
- the number, L represents the duration of the first pause event in the preset time
- R e b / _ L represents the total duration of the pause time in the preset time.
- the weighted average duration of the pause event time interval in the preset time is according to the preset time pause event and the front The time interval of a pause event and the weighting factor of the pause event are obtained.
- the specific calculation formula can be:
- MultiRebuf _ Factor ⁇ ⁇ , where; ⁇ represents the total number of pause events in the preset time, /w e rv represents the time interval between the first pause event and the previous pause event in the preset time, for example, the current pause The distance between the start time of the time and the end time of the previous pause event; the weighting coefficient indicating the first pause event (can be an equal constant, or the weight set according to the pause interval time. The longer the interval, the greater the weight, anyway The smaller the value, MultiRebuf—Factor represents the weighted average duration of the pause event interval within the preset time.
- the weighting coefficient may also be set according to a preset rule, and the preset rule includes setting according to the length of the pause event time interval or according to the number of pauses occurring within the same pause interval time.
- the horizontal axis t represents the length of the pause interval, that is, the distance between the start time of the current pause time and the end time of the previous pause event
- the vertical axis N m represents the number of pauses occurring during the same pause interval ; It can be set according to N m, and the larger the N m is, the larger the weight is.
- it may be the media reference quality or the media quality after packet loss distortion.
- the higher ⁇ 0 _ ⁇ ⁇ ⁇ the greater the decrease.
- the larger the Rebuf _ Num or Rebuf _ Len or MultiRebuf _ Factor the greater the impact of media quality and the more the media quality declines.
- the quality of the pause event distortion may be obtained according to the initial quality of the media, the number of pause events, and the duration of the pause event, and the distortion quality of the pause event is b /_N m , Rebuf _ Len , MultiRebuf _ Factor linear, Nonlinear or a combination of linear and nonlinear, the specific calculation formula of the distortion quality of the pause event may be:
- the pause event distortion quality is based on the initial quality of the media, the number of pause events, and the pause event
- e b4 (Video_Quality-MOS vm )- ' Rebif _Nm b + - Rebif _Nm dl + ) ⁇
- ⁇ ⁇ indicates the media minimum quality ( a constant greater than 0)
- b M /_N represents the number of pause events in the score segment (the media sequence within a preset period of time)
- Rebuf _ Len indicates the duration of the pause time within the score segment
- MultiRebuf _ Factor indicates the preset
- the weighted average duration of the time interval of pause events, ⁇ , ⁇ 2 , ⁇ » 2 is 1 $t.
- the specific calculation formula for determining the final quality of the media according to the obtained media reference quality and the stall quality of the pause event may be:
- Q v Q coding - Q rebuf , which represents the final quality of the media, ⁇ ⁇ represents the media reference quality, and represents the quality of the pause event distortion.
- Embodiment 2 is a diagrammatic representation of Embodiment 1:
- FIG. 3 is a flowchart showing an implementation process of a media quality assessment method according to Embodiment 2 of the present invention. The process is detailed as follows:
- step S301 the media reference quality, the acquired packet distortion quality, and the stall event distortion quality are acquired.
- the quality of the media reference and the quality of the packet loss can be obtained by using the prior art, and details are not described herein again.
- the distortion quality of the pause event is obtained by the method of the first embodiment.
- the parameters of the stall event distortion quality include at least one of the following: the number of pause events, the duration of the pause event, the interaction impact parameter of the multiple pause events, the media initial quality, and the media content complexity description factor.
- the final media quality c (whi , ⁇ . 5 ⁇ , ;> is determined according to the acquired media reference quality, the packet loss distortion quality, and the stall event distortion quality.
- the specific calculation formula for determining the final quality of the media according to the obtained media reference quality, packet loss distortion quality, and pause event distortion quality may be:
- Q rebuf [Q codmg - MOS ⁇ ) - func (Rebuf_Num, Rebuf_Len, MultiRebuf_F actor) '
- Q v denotes the final quality of the media, which indicates the quality of the media reference, which indicates the quality of the packet loss distortion, and indicates the quality of the distortion of the pause event.
- the initial quality of the media is also calculated according to the obtained media reference quality and the quality of the packet loss distortion, and the quality of the suspended event is obtained according to the obtained event.
- Q rebuf ⁇ Video _ Quality - MOS ⁇ ) ⁇ func [Rebuf_N urn, Rebuf_Len, MultiRebuf_F actor) and the calculated media initial quality to determine the final quality of the media.
- Embodiment 3 is a diagrammatic representation of Embodiment 3
- FIG. 4 is a flowchart showing an implementation process of a media quality assessment method according to Embodiment 3 of the present invention. The process is detailed as follows:
- step S401 the media reference quality and the pause event distortion quality are obtained.
- the parameter of the quality of the pause event includes the initial quality of the media, the number of pause events, the duration of the pause event, and the media content complexity description factor Q rebuf - func ⁇ Video Quality, Rebuf Num, Rebuf Lm, Complexity Factor ) or
- the parameters of the stop event distortion quality include the number of pause events, the duration of the pause event And the media content is complex
- Q rebuf func ⁇ Rebuf _ Num, Rebuf _ Len, Complxity - Factor); or the parameter of the pause event distortion quality includes the number of pause events, the duration of the pause event, the interaction effect of multiple pause events
- Q rebuf func [Rebuf _ Num, Rebuf _ Len, MultiRebuf _ Factor, Complxity _ Factor).
- the pause information in the first embodiment including Rebuf_Num, Rebuf_Len, Factor
- media initial quality combined with the media content complexity description factor to calculate the stall event distortion quality.
- the quality of the pause event distortion is obtained according to the initial quality of the media, the number of pause events, the duration of the pause event, and the media content complexity description factor, and the specific calculation formula may be:
- the quality of the mediation of the pause event is obtained according to the initial quality of the media, the number of pause events, the duration of the pause event, the interaction parameter of the multiple pause event, and the media content complexity description factor, and the specific calculation formula may be :
- Video _ Quality is the media initial quality
- MO ⁇ n is the media minimum quality
- Rebuf _ Num is the number of pause events in the preset time
- R e b / _ L is the duration of the pause time in the preset time
- MultiRebuf _ Factor Indicates the weighted average duration of the pause interval in the preset time.
- CompZe; y _ 3 ⁇ 4ctor indicates the complexity of the media content in each preset time period, ⁇ , ⁇ is a constant.
- FIG. 5 is a flowchart showing an implementation process of a media quality assessment method according to Embodiment 4 of the present invention. The process is detailed as follows:
- step S501 the media reference quality, the lost packet distortion quality, and the stall event distortion quality are acquired.
- the quality of the media reference and the quality of the packet loss can be obtained by using the prior art, and details are not described herein again.
- the distortion quality of the pause event is obtained by the method of the third embodiment.
- the parameters of the quality of the pause event include the media initial quality, the number of pause events, the duration of the pause event, and the media content complexity description factor.
- the parameter of the stop event distortion quality includes media initial quality, number of pause events, pause event Duration, multiple pause event interaction influence parameters, and media content complexity description factor
- Q rebuf (Video _ Quality - MOS ⁇ ) ⁇ func ⁇ Rebuf _ Lm, Rebuf _ Num, MultiRebuf _ Factor) ⁇ The said •fund ( Complexity _ Factor).
- the quality of the pause event distortion can be obtained according to the initial quality of the media, the number of pause events, the duration of the pause event, and the media content complexity description factor;
- the quality of the pause event distortion is obtained according to the initial quality of the media, the number of pause events, the duration of the pause event, the interaction impact parameter of the multiple pause events, and the media content complexity description factor;
- the quality of the pause event distortion is obtained according to the number of pause events, the duration of the pause event, and the media content complexity description factor;
- the pause event distortion quality is obtained according to the number of pause events, the pause event duration, the multiple pause event interaction influence parameters, and the media content complexity description factor.
- Embodiment 5 is a diagrammatic representation of Embodiment 5:
- FIG. 6 is a flowchart showing an implementation process of a media quality assessment method according to Embodiment 5 of the present invention. The process is detailed as follows:
- step S601 the media file to be evaluated is divided into a plurality of scoring segments.
- the media file to be evaluated is divided into a plurality of rating segments according to a pause event or a pause time.
- step S602 the media reference quality and the pause event distortion quality of each of the score segments are obtained, and the parameters of the pause event distortion quality of the score segment include at least one of the following: the number of pause events, the pause event duration, and the multiple pause events. Interactions affect parameters, media initial quality, and media content complexity description factors.
- step S603 the media quality of each of the score segments is calculated according to the acquired media reference quality and the stall event distortion quality of each of the score segments.
- the media quality of each score segment can be obtained by using the media quality calculation method of the first, second, third or fourth embodiment to obtain 3 ⁇ 4, Q) f.
- a weight is set for each score segment according to the pause duration of each score segment pause event, or a weight is set for each score segment according to each score segment pause quality score or a pause model impact factor;
- the media quality of the N score segments is lower than the preset media quality, the lowest media quality of the N score segments or the average of the N score segment media qualities is used as the final quality of the media, where The N is greater than or equal to an integer of 1.
- Fig. 7 is a view showing the configuration of a medium quality evaluation apparatus according to a sixth embodiment of the present invention. For the convenience of description, only parts related to the embodiment of the present invention are shown.
- the media quality evaluation device can be applied to various information terminals (television, mobile phone, computer, personal digital assistant, etc.), and can be a software unit, a hardware unit or a combination of hardware and software running in these terminals, or As independent pendants integrated into these terminals or in the application system of these terminals.
- the media quality evaluation device 7 includes an acquisition unit 71 and a determination unit 72. Among them, the specific functions of each unit are as follows:
- the obtaining unit 71 is configured to obtain media reference quality and pause event distortion quality
- a determining unit 72 configured to determine a media final quality according to the media reference quality acquired by the acquiring unit 71 and the quality of the stall event distortion;
- the parameters of the pause event distortion quality include at least one of the following: the number of pause events, the pause event duration, the multiple pause event interaction influence parameters, the media initial quality, and the media content complexity. Description factor.
- the acquiring unit 71 is further configured to acquire a packet loss distortion quality.
- the determining unit 72 is further configured to determine a media final quality according to the media reference quality, the packet distortion quality, and the stall event distortion quality acquired by the acquiring unit 71.
- the determining unit 72 is specifically configured to calculate a media initial quality according to the obtained media reference quality and packet loss distortion quality, and then determine a media final quality according to the obtained pause event distortion quality and the calculated media initial quality.
- the quality of the pause event is obtained according to the initial quality of the media, the number of pause events, and the duration of the pause event; or the quality of the pause event is based on the initial quality of the media, the number of pause events, and the duration of the pause event.
- the multiple pause event interaction affects the parameter obtaining; or, the pause event distortion quality is obtained according to the media initial quality, the number of pause events, the pause event duration, and the media content complexity description factor; or, the pause event distortion quality Obtaining according to the media initial quality, the number of pause events, the pause event duration, the multiple pause event interaction influence parameter, and the media content complexity description factor; or, the pause event distortion quality is based on the pause event number, the pause event duration And the media content complexity description factor is obtained; or, the pause event distortion quality is described according to the number of pause events, the duration of the pause event, the interaction parameter of the multiple pause events, and the complexity of the media content. Son get.
- the duration of the pause event is a weighted average duration of the pause event in the preset time period, and the weighted average duration of the pause event in the preset time period is obtained according to the duration of the pause event in the preset time period and the weighting coefficient of the pause event; or
- the duration of the pause event is the ratio of the total duration of the pause event to the preset time in the preset time; or the duration of the pause event is the total duration of the pause time in the preset time.
- the multiple pause event interaction influence parameter is a weighted average duration of the pause event interval in the preset time, and the weighted average duration of the pause event interval in the preset time is based on the pause event and the previous time in the preset time
- the time interval of the pause event and the weighting factor of the pause event are paid.
- the weighting factor is set according to the length of the pause event time interval or according to the number of times of the same pause interval.
- the media quality evaluation apparatus may use the foregoing corresponding media quality evaluation method.
- the media quality evaluation apparatus may use the foregoing corresponding media quality evaluation method.
- Fig. 8 is a view showing the configuration of a medium quality evaluation apparatus according to a seventh embodiment of the present invention. For the convenience of description, only parts related to the embodiment of the present invention are shown.
- the media quality evaluation device can be applied to various information terminals (television, mobile phone, computer, personal digital assistant, etc.), and can be a software unit, a hardware unit or a combination of hardware and software running in these terminals, or As independent pendants integrated into these terminals or in the application system of these terminals.
- the media quality evaluation apparatus 8 includes a scoring section dividing unit 81, an obtaining unit 82, a calculating unit 83, and a determining unit 84. Among them, the specific functions of each unit are as follows:
- a scoring segment dividing unit 81 configured to divide the media file to be evaluated into a plurality of scoring segments; and an obtaining unit 82, configured to acquire media benchmark quality and pause of each of the scoring segments divided by the scoring segment dividing unit 81
- the event distortion quality, the parameter of the stall event distortion quality of the score segment includes at least one of the following: a number of pause events, a pause event duration, a plurality of pause event interaction influence parameters, a media initial quality, and a media content complexity description factor;
- the calculating unit 83 is configured to calculate, according to the media reference quality and the pause event distortion quality of each of the score segments acquired by the obtaining unit 82, the media quality of each of the score segments divided by the score segment dividing unit 81;
- the determining unit 84 is configured to determine a final quality of the media according to the media quality of each of the score segments calculated by the calculating unit 83.
- the score segment dividing unit 81 is specifically configured to divide the media file to be evaluated into multiple score segments according to the pause event or the pause time.
- the determining unit 84 includes:
- the weight setting module 841 is configured to set a weight for each score segment according to a pause duration of each score segment pause event, or set a weight for each score segment according to each score segment pause quality score or a pause model impact factor;
- a determining module 842 configured to perform a weighting operation on a media quality of each scoring segment of the media according to the weight set by the weight setting module 841, and use a weighted average obtained by the weighting operation as a final of the media quality.
- the determining unit 84 is configured to use the lowest media quality of the N score segments or the N score segment media qualities. Mean as the final quality of the media, wherein the N is greater than or equal to 1
- the media quality evaluation apparatus provided in this embodiment may use the foregoing corresponding media quality evaluation method.
- the media quality evaluation apparatus may use the foregoing corresponding media quality evaluation method.
- each unit and module included in the foregoing embodiments 6 and 7 is only divided according to functional logic, but is not limited to the above division, as long as the corresponding functions can be implemented;
- the specific names of the functional units and modules are also for convenience of distinguishing from each other and are not intended to limit the scope of the present invention.
- the embodiment of the present invention considers the influence of multiple pause event interaction influence parameters, media initial quality, and media content complexity description factor on media quality when calculating media quality, so that the media quality evaluation result is more accurate. , more consistent with people's subjective feelings.
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Priority Applications (6)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
EP12878144.0A EP2830316B1 (en) | 2012-05-28 | 2012-12-02 | Method and device for evaluating media quality |
JP2015512994A JP6099107B2 (ja) | 2012-05-28 | 2012-12-02 | メディア品質を評価するための方法および装置 |
SG11201406655UA SG11201406655UA (en) | 2012-05-28 | 2012-12-02 | Method and apparatus for evaluating media quality |
BR112014029458-5A BR112014029458B1 (pt) | 2012-05-28 | 2012-12-02 | Método e aparelho para avaliar qualidade de mídia |
KR1020147031766A KR101693564B1 (ko) | 2012-05-28 | 2012-12-02 | 미디어 품질 평가 방법 및 장치 |
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CN114640884A (zh) * | 2022-03-21 | 2022-06-17 | 武汉庆实广告传媒有限公司 | 一种在线视频播放质量分析方法、系统及计算机存储介质 |
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CN104052991A (zh) * | 2014-06-17 | 2014-09-17 | 德科仕通信(上海)有限公司 | 检测has视频卡顿的方法及系统 |
US10271112B2 (en) * | 2015-03-26 | 2019-04-23 | Carnegie Mellon University | System and method for dynamic adaptive video streaming using model predictive control |
CN106911927B (zh) * | 2015-12-23 | 2020-05-01 | 中国移动通信集团公司 | 评估网络视频用户体验质量的方法、装置和dpi设备 |
CN107105224A (zh) * | 2017-03-24 | 2017-08-29 | 深圳信息职业技术学院 | 一种视频体验质量评估的方法、装置与系统 |
CN108376147B (zh) * | 2018-01-24 | 2021-09-28 | 北京一览科技有限公司 | 一种用于获得视频的评价结果信息的方法和装置 |
CN108389592B (zh) * | 2018-02-27 | 2021-10-08 | 上海讯飞瑞元信息技术有限公司 | 一种语音质量评价方法及装置 |
CN109600508B (zh) * | 2018-04-10 | 2019-08-30 | 利辛县雨若信息科技有限公司 | 手机播放故障自查方法 |
CN108650407B (zh) * | 2018-04-10 | 2019-04-26 | 新昌县智创机械有限公司 | 手机播放故障自查平台 |
CN109729433B (zh) * | 2019-01-22 | 2021-05-07 | 北京奇艺世纪科技有限公司 | 一种视频播放评估方法及装置 |
CN112689200B (zh) * | 2020-12-15 | 2022-11-11 | 万兴科技集团股份有限公司 | 视频编辑方法、电子设备及存储介质 |
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EP2830316A1 (en) | 2015-01-28 |
CN103458264B (zh) | 2015-02-25 |
BR112014029458A8 (pt) | 2021-06-15 |
EP2830316B1 (en) | 2016-04-27 |
BR112014029458B1 (pt) | 2022-06-14 |
KR101693564B1 (ko) | 2017-01-06 |
CN103458264A (zh) | 2013-12-18 |
US9654770B2 (en) | 2017-05-16 |
HK1190844A1 (zh) | 2014-07-11 |
SG11201406655UA (en) | 2014-12-30 |
JP6099107B2 (ja) | 2017-03-22 |
JP2015523774A (ja) | 2015-08-13 |
EP2830316A4 (en) | 2015-03-11 |
KR20150003316A (ko) | 2015-01-08 |
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