CN101448175B - Method for evaluating quality of streaming video without reference - Google Patents
Method for evaluating quality of streaming video without reference Download PDFInfo
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- CN101448175B CN101448175B CN2008102076955A CN200810207695A CN101448175B CN 101448175 B CN101448175 B CN 101448175B CN 2008102076955 A CN2008102076955 A CN 2008102076955A CN 200810207695 A CN200810207695 A CN 200810207695A CN 101448175 B CN101448175 B CN 101448175B
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Abstract
The invention discloses a method for evaluating quality of streaming video without reference. The method is realized in a simulation environment of simulating network loss on MPEG-TS stream; network damage is simulated through man-made loss, simultaneously loss data is recorded, attribute of the data is analyzed, an image of the loss is stored, and impact to visual effect after the data loss is observed by eye, thereby establishing a one-to-one correspondence. In practical application, a QOE evaluation value which is in accord with subjective feeling of a user can be acquired through sampling and analyzing a transmission media and analyzing the network damage. In the method, video flowing is directly analyzed without source file information, analysis process is simple and complex algorithm is not needed, quality of user experience is reflected in real time and an accurate evaluation value is given, and an objective evaluation method and a subjective evaluation method are combined to ensure the evaluation value is closer to the real feeling of the user.
Description
Technical field
The present invention relates to the technical field of user's service experience (QoE), specifically a kind of method for evaluating quality of streaming video that does not have reference.
Background technology
The epoch of 3G (third generation) finally this means that the speed of transmission voice and data promotes greatly, and it can handle multiple media formats such as image, music, video flowing, and multiple information services such as comprising web page browsing, videoconference, ecommerce is provided.So the range of application of video on network is more and more wider, such as film-on-demand, remote teaching, video conference or the like.And with different being of 2G (second generation) another one, the professional successful key of 3G is to see the quality of user's Quality of experience (QoE), intense market competition is recognized operator: improve terminal use's satisfaction, keeping user and the scale of extending one's service here is the key of existence and profit.Therefore notion and the correlative study of QoE are arisen at the historic moment.
The main appraisal procedure of QoE has two big classes at present, comprises two kinds of subjective evaluation and objective evaluations, and wherein objective evaluation is divided into full reference, partial reference again and does not have with reference to three kinds of methods.Subjective evaluation method real-time is bad, and will expend lot of manpower and material resources, can not be directly used in the video quality assessment in the streaming media service usually.In the objective evaluation, full reference method is the most accurate a kind of, and its precondition is to obtain the complete source video, then each pixel is compared one by one.On the one hand, it is bigger to obtain source video difficulty in the stream Video Applications, and on the other hand, relatively time complexity is very big one by one for pixel, these factors have greatly limited the usable range of this method, so not strong for the video quality assessment operability in the packet network.Second method is the partial reference method, having extracted some characteristic informations of original compression and reconstructing video assesses, this method equally need about source file 14% data volume, its shortcoming is that complexity is bigger relatively and spend bigger network overhead than no reference method.And simple available be no reference method, promptly need be from the information of source video, analyze according to transport stream, draw the user experience assessment result, its real-time height, resource overhead are little, need not by decoder video flowing to be decoded, and can monitor in real time at the heterogeneous networks point.Though the accuracy of the disappearance of source video information meeting impact evaluation, this method is the most simple.And to the objective evaluation method generally speaking, can't the complete reaction user experience quality.Because value of QoE, must the encompasses users experience sense be subjected to the subjective factor of aspect with subjective characteristic.
Summary of the invention
The purpose of this invention is to provide a kind of method for evaluating quality of streaming video that does not have reference, this method is to realize a simulated environment to MPEG-TS (real-time video transmission that dynamic image expert group formulates fail to be sold at auction standard) flow field simulation Network Packet Loss, need not the reference source file, only transport stream is carried out simple analysis, just can provide the value of QoE more accurately that meets user's subjective feeling in real time.
The object of the present invention is achieved like this:
A kind of method for evaluating quality of streaming video that does not have reference, this method need realize a simulated environment to MPEG-TS flow field simulation Network Packet Loss, come the analog network damage by artificial packet loss, write down the packet loss data simultaneously, analyze its attribute, and preserve packet loss place image, the influence that behind the eye-observation obliterated data visual effect is produced, thereby set up a kind of relation one to one, in actual applications, just can damage by phase-split network by the sampling analysis transmission medium, acquisition meets the QOE assessed value of user's subjective feeling, the concrete operations step:
The first step: packet loss (needing repeatedly to repeat, up to the decision relation that draws between packet loss and the video quality damage situations) manually is set.
Second step: according to the packet loss of setting, software carries out packet loss at random by giving out a contract for a project.
The 3rd step: preserve the packet loss data.
The 4th step: use ready-made open source software that packet loss place frame is saved as jpeg file.
The 5th step: the packet loss rear video is preserved separately.
The 6th step: the image head of scanning packet loss place frame, to discern this frame by image encoding type identification position and belong to the I frame, the B frame still is the P frame, if the I frame skipped for the 7th step.
The 7th step: P frame and B frame macro block characteristics are analyzed, and by scanning the additional information of macro block by turn, the sign position of macroblock encoding type are arranged wherein, thereby obtain this macroblock encoding type.The macroblock encoding type of P frame has two kinds: internal type (differing greatly with the reference frame content) and forward direction type (little with reference frame content difference); Macroblock encoding type in the B frame has 4 kinds: internal type (all bigger with front and back reference frame content difference), forward direction type are (little with the content difference of front reference frame, differ greatly with the content of back reference frame), the back to type (differing greatly with the content of front reference frame, little), bi-directional type (all little) with front and back reference frame content difference with the content difference of back reference frame.
The 8th step: human eye is watched whole impaired video.
The 9th step: the data characteristics of the seven, eight step gained is associated with the human eye viewing effect of the 8th step gained, thereby sets up corresponding relation between packet loss and the video integral body damage situations.
The tenth step: the impaired vision situation of eye-observation packet loss place frame and consecutive frame, record result.
The 11 step: set up the mapping relations of obliterated data feature and impaired vision situation, according to this just by Network Packet Loss situation predicted video quality.
The present invention was further characterized in that for the 7th step and the 11 step, used the appraisal procedure of no reference, and subjectiveness and objectiveness is combined.
Compare with background technology, the present invention has following advantage:
(1), Yi Hangxing: do not need the reference source file.Because at first, then the corresponding relation that draws a data degree of impairment and impaired vision situation is analyzed in this damage by local MPEG-TS stream file being carried out artificial packet loss analog network damage.Like this, in actual application, no longer need original video files, only need to analyze the Streaming Media in the transmission course, analyze its network harm situation, thereby just can obtain corresponding impaired vision situation.Very simple.Unlike traditional full reference or partial reference method, needing to obtain original video information could be by relatively drawing the QOE value.
(2), simplicity: this method has been utilized the characteristics of MPEG2 (a kind of audio/video encoding standard that dynamic image expert group formulates) coding standard, only need identify the position by the video coding mode in the scanning frame head and just can obtain this frame type.Equally, can obtain the feature of macro block equally by the macroblock encoding type of macroblock layer.And the subjective method that the video quality of impaired picture adopts human eye to watch is very simple.
(3), real-time: this method is to damage the corresponding relation that draws between loss of data and the visual effect by analog network in advance, but be a ready-made normative reference, in actual applications, can directly adopt this standard, only need stochastical sampling, the phase-split network degree of impairment just can obtain the QOE value in real time, and offer the user.
(4), subjective and objective combining: the objective evaluation method that this method will not have reference combines with the subjective evaluation method of eye-observation.The on the one hand damage that causes by phase-split network obtains packet loss, the attribute of packet loss data, thus obtain the objective damage situations of video; On the other hand, by the impaired picture of eye-observation, draw the accepted situation of user to this damage situations, then that two kinds of results are comprehensive, draw the QOE value near the user, this has just remedied the deficiency that simple subjective evaluation method and single objective evaluation method exist separately in the conventional method.
Description of drawings
Fig. 1 is a structure chart of the present invention
Fig. 2 implements flow chart of the present invention
Embodiment
Now be described with reference to the accompanying drawings technical scheme of the present invention:
Embodiment
The present invention need be in a simulated environment, by the MPEG-TS file is carried out artificial packet loss, the analog network damage, then with the packet loss data, MPEG-TS file behind the packet loss, and packet loss place frame and consecutive frame are preserved the jpeg image file that forms preserve, analyze obtains packet loss and obliterated data feature and the visual effect mapping relations between damaging, evaluates video quality according to this, the concrete operations step:
The first step: packet loss (%) manually is set.
Second step: according to the packet loss of setting, software carries out packet loss at random by giving out a contract for a project.
The 3rd step: preserving the bag data conversion storage of losing is jpeg file.
The 4th step: packet loss place frame is saved as jpeg file.
The 5th step: the packet loss rear video is saved as video separately.
The 6th step: the image head of scanning packet loss place frame, to discern this frame by image encoding type designation position and belong to the I frame, the B frame still is the P frame, and shows on the interface, and judges whether the I frame, if, skipped for the 7th step, if not, carried out for the 7th step.
The 7th step: analyze the packet loss data, obtain macro block characteristics, and in interface display.
The 8th step: use the video after software VLC (video local area network (LAN) client) plays packet loss, the human eye viewing effect.
The 9th step: the JPEG picture of the conversion of eye-observation packet loss place frame and consecutive frame draws the degree of injury result.
The tenth step: record result.
The 11 step: repeatedly repeat ten steps of the first step to the, enough up to data.
The 12 step: draw packet loss, and the mapping relations between lost data packets feature and the video quality damage, according to this just can be according to Network Packet Loss situation predicted video quality.
The 13 step: finish.
Claims (1)
1. method for evaluating quality of streaming video that does not have reference, be in a simulated environment, carry out artificial packet loss by accurate MPEG-TS file that the real-time video transmission of dynamic image expert group formulation is failed to be sold at auction, the analog network damage, then with the packet loss data, the real-time video transmission that dynamic image expert group behind the packet loss the formulates accurate MPEG-TS file of failing to be sold at auction, packet loss place frame and consecutive frame are preserved the JPEG (joint photographic experts group) Joint Photographic Experts Group image file that forms and are preserved, analyze, obtain the mapping relations between the damage of packet loss and obliterated data feature and visual effect, just obtain the foundation of a cover evaluates video quality, just can be according to the real-time network situation according to this mapping relations predicted video quality, its concrete steps are as follows:
The first step: packet loss manually is set;
Second step: according to the packet loss of setting, software carries out packet loss at random by giving out a contract for a project;
The 3rd step: is the bag data conversion storage of losing jpeg file;
The 4th step: packet loss place frame is saved as jpeg file;
The 5th step: the packet loss rear video is saved as video separately;
The 6th step: the image head of scanning packet loss place frame, discern this frame category by image encoding type designation position, belong to the I frame, the B frame still is the P frame, and on the interface, show, and judge whether the I frame, if skipped for the 7th step; If not, carried out for the 7th step;
The 7th step: analyze the packet loss data, obtain macro block characteristics, and in interface display;
The 8th step: use the video after video local area network (LAN) client VLC software is play packet loss, the human eye viewing effect;
The 9th step: the jpeg file in the 4th step of eye-observation draws the degree of injury result;
The tenth step: record result;
The 11 step: repeatedly repeat ten steps of the first step to the, enough up to data;
The 12 step: draw the mapping relations between the damage of packet loss and lost data packets feature and video quality, according to this just can be according to Network Packet Loss situation predicted video quality;
The 13 step: finish.
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Families Citing this family (20)
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| CN101998137B (en) * | 2009-08-21 | 2016-09-07 | 华为技术有限公司 | Video quality parameter acquisition methods and device and electronic equipment |
| CN101938760B (en) * | 2010-08-20 | 2013-05-01 | 中国电信股份有限公司 | Method and system for dialing test of perceptions of video service users |
| CN102006497B (en) * | 2010-11-16 | 2013-06-12 | 江南大学 | No-reference blurred image evaluation method based on local statistical characteristics of images |
| CN102572501A (en) * | 2010-12-23 | 2012-07-11 | 华东师范大学 | Video quality evaluation method and device capable of taking network performance and video self-owned characteristics into account |
| US8441955B2 (en) * | 2011-01-24 | 2013-05-14 | Tektronix, Inc. | Determining mobile video quality of experience and impact of video transcoding |
| CN102075784B (en) * | 2011-02-18 | 2012-11-28 | 中国传媒大学 | Video quality assessment method under condition of comprehensively considering compression and packet loss impairment |
| CN102740108B (en) * | 2011-04-11 | 2015-07-08 | 华为技术有限公司 | Video data quality assessment method and apparatus thereof |
| CN103312531B (en) | 2012-03-15 | 2017-02-22 | 华为技术有限公司 | Quality of experience (QOE) acquiring method, device and QOE guaranteeing method and device |
| CN103634594B (en) | 2012-08-21 | 2015-04-29 | 华为技术有限公司 | Method and apparatus for obtaining video coding compression quality |
| CN103945213B (en) * | 2013-01-22 | 2016-12-28 | 中兴通讯股份有限公司 | A kind of video flow quality monitoring method and device |
| CN103581661B (en) * | 2013-10-28 | 2015-06-03 | 宁波大学 | Method for evaluating visual comfort degree of three-dimensional image |
| CN103841410B (en) * | 2014-03-05 | 2016-05-04 | 北京邮电大学 | Based on half reference video QoE objective evaluation method of image feature information |
| CN104320296B (en) * | 2014-09-30 | 2017-10-03 | 深圳市云之讯网络技术有限公司 | The assessment detection method and its device of a kind of network quality |
| CN104581140B (en) * | 2014-12-26 | 2016-08-24 | 国家电网公司 | A kind of video quality evaluation method of video conferencing |
| CN105828064B (en) * | 2015-01-07 | 2017-12-12 | 中国人民解放军理工大学 | The local video quality evaluation without reference method with global space-time characterisation of fusion |
| CN106713901B (en) * | 2015-11-18 | 2018-10-19 | 华为技术有限公司 | A kind of method for evaluating video quality and device |
| CN106878086A (en) * | 2017-03-06 | 2017-06-20 | 北京理工大学 | A kind of VoLTE video callings user experience quality appraisal procedure |
| CN107027023B (en) * | 2017-04-24 | 2018-07-13 | 北京理工大学 | Based on the VoIP of neural network without reference video communication quality method for objectively evaluating |
| CN107464222B (en) * | 2017-07-07 | 2019-08-20 | 宁波大学 | Based on tensor space without reference high dynamic range images method for evaluating objective quality |
| US20190238856A1 (en) * | 2018-01-31 | 2019-08-01 | Hewlett Packard Enterprise Development Lp | Estimating video quality of experience |
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