CN103475951A - User-experience-based real-time video transmission rate self-adaption method - Google Patents
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Abstract
The invention discloses a user-experience-based real-time video transmission rate self-adaption method which can self-adaptively perform video transmission rate adaption according to network characteristics and user experience. In the method, a mobile acquisition terminal, a playing client terminal and an adaptive server are arranged. The mobile acquisition terminal is used for acquiring real-time video data, the playing client terminal is used for receiving and playing videos and the adaptive server is used for monitoring the network conditions of the mobile acquisition terminal and the playing client terminal and the type of the videos acquired by the mobile acquisition terminal, simultaneously receiving user experience grades fed back by a playing client, and then deciding the currently best sending bit rate by adopting an adaptive algorithm according to parameters, and informing the mobile acquisition terminal of regulating the sending bit rate. Different from a method of transmitting the videos with the constant sending bit rate, the user-experience-based real-time video transmission rate self-adaption method can self-adaptively regulate the video sending bit rate according to the real-time network conditions and the user experience, thus providing relatively good experience for a user.
Description
Technical field
The invention belongs to the adaptive video transmission technique field, relate to a kind of real-time video transmission adaptive approach, is mainly to carry out adaptation for the transmission of video bit rate.
Background technology
along with the wireless and high speed development mobile network, the application and development of streaming media service on mobile terminal also more and more receives much concern.Yet the mobile network is a time varying channel, how, according to the continuous variation of network condition, the adaptive transmission of carrying out the Streaming Media real time data, improve stream media transmission quality and become the significant problem that current urgent need solves.
Simultaneously, user end to end in streaming media service experiences (Quality of Experience, QoE) also more and more receive operator and users' attention, QoE is the overall merit of quality to accept service as the user, in close relations relevant to terminal use, business and content supplier, network and service provider, equipment manufacturers.By the research to QoE and the application in real network, can improve network quality, improve the service quality that the user experiences.Therefore necessary when the adaptive stream media service is provided, add the QoE factor, for the user provides better service experience.
Summary of the invention
technical problem:the objective of the invention is to overcome the deficiency of existing streaming media service transmission technology, provide a kind of in the real-time video transmission process, experience the method for the video Transmit Bit Rate being carried out to the self adaptation adaptation according to network condition, video type, user.
technical scheme:the real-time video transmission rate adaptation adaptation method of experiencing based on the user of the present invention, the method is by the mobile collection end, the network that client end of playing back and adaptation services device three parts form, can experience the transmission rate that QoE scoring dynamic self-adapting ground changes the mobile collection end according to mobile collection end and the residing network environment of client end of playing back, the type of transmission of video and the user of user feedback, concrete steps are as follows:
A) the adaptation services device is carried out to initialization, monitored at the port of appointment, prepare to receive the real time data information from mobile collection end and client end of playing back.
B) the mobile collection end is carried out to initialization, start to monitor the type of self network condition and transmission of video, and network strength, link rate information and motion state information exchange of living in are crossed to socket (socket) communication be sent to the adaptation services device.Client end of playing back is carried out to initialization, start to monitor self network condition, and network strength, link rate information are sent to the adaptation services device.
C) client end of playing back is initiated the transmission of video request to the mobile collection end, starts to transmit real time video data between the two; The adaptation services device is opened adaptation services, experience the QoE scoring according to the network signal intensity of current mobile collection end, the type of transmission of video, the network signal intensity of client end of playing back and the user of user feedback, by the adaptation algorithm decision-making, go out to be applicable to the best Transmit Bit Rate of the present situation and be sent to the mobile collection end.
D) after the mobile collection termination is received, Transmit Bit Rate is adjusted into to this best Transmit Bit Rate value, the video data that client end of playing back receives after adjusting is watched.
In the present invention, the mobile collection end comprises three modules: Transmit Bit Rate is adaptive, network condition is monitored, the transmission of video type identification.Client end of playing back comprises two modules: network condition detects, the user experiences the QoE scoring.The adaptation services device consists of adaptive decision-making module.Wherein, the Transmit Bit Rate adaptation module is used for receiving the transmission rate value after adaptive decision-making, and the transmission rate of mobile collection end is adjusted into to this value; The network condition monitoring modular is for being monitored the signal strength signal intensity of mobile collection end or the residing network of client end of playing back in the transmission of video process, and the network strength value is sent to the adaptation services device carries out adaptation; Transmission of video type identification module is used for judging the motion state of mobile collection end, and sends it to the parameter of adaptation services device as adaptation algorithm.The user experiences the QoE grading module and video quality is given a mark in the process of watching video for the user, and this value is fed back to the adaptation services device to carry out adaptation services; Adaptive decision-making module is responsible for receiving the every data message from mobile collection end and client end of playing back, comprehensive adaptive decision-making.
Form traditional client server mode between mobile collection end of the present invention, client end of playing back and adaptation services device, realize communicating by letter between client-server by socket.
The parameter of adaptation algorithm of the present invention comprises that mobile collection end network signal intensity, client end of playing back network signal intensity, mobile collection end transmission of video type, the real-time user of client experience 4 parameters of QoE scoring.Concrete adaptation algorithm is as follows: first the network condition of mobile collection end and client end of playing back is divided into to some grades according to its span, as S1, S2, S3, S4,5 ranks of S5; Again by Transmit Bit Rate (Send Bit Rate, SBR) carry out corresponding classification, as A, B, C, D, 5 ranks of E, then judge according to the occurrence of the network signal intensity of current mobile collection end and client end of playing back the rank that it is corresponding, and map out its corresponding Transmit Bit Rate rank.After determining the rank of SBR, then experience according to type and the user of current transmission video the occurrence that QoE marks to determine Transmit Bit Rate.
Client end of playing back is when watching real-time video, can be given a mark to the quality of current video, be that the user experiences the QoE scoring, and this scoring is fed back to adaptation services device end, if the threshold value of QoE scoring is experienced in this scoring lower than minimum user, trigger at once adaptation algorithm and adjust current video Transmit Bit Rate, otherwise using this scoring as the parameter value of Adaptive Rate Shape next time.
beneficial effect:the present invention compared with prior art, has the following advantages:
The present invention is different from the adaptation method of only considering transmitting terminal or the one-side network condition of receiving terminal in existing adaptation technique, but the network condition of comprehensive transmitting terminal and receiving terminal is carried out adaptation, for the user provides most suitable video quality, reduced the packet loss of network.The present invention simultaneously experiences the QoE scoring as adaptive key factor using the user of user feedback, can carry out the adjustment of video rate according to user's evaluation, from user perspective, can provide better service experience for the user.The present invention is based on smart mobile phone and the notebook computer exploitation used in daily life, cost is lower, and adaptation algorithm used is simple, easily realizes, can be applicable to, in small-sized end-to-end RTP Transport System for Real-time, to have certain practical value.
The accompanying drawing explanation
fig. 1 is the network model figure that the present invention is based on the real-time video transmission rate adaptation adaptation of user's experience.
Fig. 2 is the scheme realization figure that the present invention is based on the real-time video transmission rate adaptation adaptation of user's experience.
The workflow diagram that Fig. 3 is adaptation services device of the present invention.
Fig. 4 is adaptation algorithm flow chart of the present invention.
Embodiment
Below in conjunction with accompanying drawing, the inventive method is described in further detail.
The real-time video transmission speed self-adaption method of experiencing based on the user of the present invention, be to be based upon as shown in Figure 1, by the mobile collection end, and the network model that client end of playing back and adaptation services device three parts form.The mobile collection end can be smart mobile phone; Client end of playing back can be that notebook computer can be also mobile terminal, as smart mobile phone, and panel computer etc.; The adaptation services device can be built on notebook computer.The mobile collection end is responsible for the collection of real time video data, the video flowing that client end of playing back receives for remote playing, the adaptation services device mainly is responsible for collecting the network signal intensity data of these two, the motion state data of mobile collection end and the user who is fed back by client end of playing back and is experienced the QoE scoring, comprehensive these parameters carry out adaptive decision-making and obtain current optimum Transmit Bit Rate value, and notice mobile collection end carries out corresponding transmission rate adjustment.
The real-time video transmission speed self-adaption method of experiencing based on the user of the present invention, experience the QoE scoring according to mobile collection end and the residing network environment of client end of playing back, the type of transmission of video and the user of user feedback, dynamic self-adapting ground changes the transmission rate of mobile collection end, as shown in Figure 3, concrete steps are as follows:
A) the adaptation services device is carried out to initialization, monitored at the port of appointment, prepare to receive the real time data information from mobile collection end and client end of playing back.The real time data information of mobile collection end client end of playing back can have type of sports, video data transmitting transmission rate of intensity, link rate, the collection video data of network signal etc.; The real time data information of client end of playing back can have intensity, link rate, the real-time user of network signal to experience QoE score information etc.
B) the mobile collection end is carried out to initialization, start to monitor self network condition and moving state, and network strength, link rate information and motion state information exchange of living in are crossed to socket (socket) communication be sent to the adaptation services device.The client end of playing back initialization, start to monitor self network condition, and network strength, link rate information are sent to the adaptation services device.
C) client end of playing back is initiated the transmission of video request to the mobile collection end, start to transmit real time video data between the two, the adaptation services device is opened adaptation services, experiences the QoE scoring according to the user of the network signal intensity of the network signal intensity of current mobile collection end, motion state, client end of playing back and user feedback and goes out to be applicable to the best Transmit Bit Rate of the present situation and be sent to the mobile collection end by the adaptation algorithm decision-making.
D) after the mobile collection termination is received, Transmit Bit Rate is adjusted into to this best Transmit Bit Rate value, the video data that client end of playing back receives after adjusting is watched.
As shown in Figure 2, in the present invention, the mobile collection end comprises three modules: Transmit Bit Rate is adaptive, network condition is monitored, the transmission of video type identification.Client end of playing back comprises two modules: network condition detects, the user experiences the QoE scoring.The adaptation services device consists of adaptive decision-making module.Wherein, the Transmit Bit Rate adaptation module is used for receiving the transmission rate value after adaptive decision-making, and the transmission rate of mobile collection end is adjusted into to this value; The network condition monitoring modular is for being monitored the signal strength signal intensity of mobile collection end or the residing network of client end of playing back in the transmission of video process, and the network strength value is sent to the adaptation services device carries out adaptation; Transmission of video type identification module is used for judging the motion state of mobile collection end, and sends it to the parameter of adaptation services device as adaptation algorithm.The user experiences the QoE grading module and video quality is given a mark in the process of watching video for the user, and this value is fed back to the adaptation services device to carry out adaptation services; Adaptive decision-making module is responsible for receiving the every data message from mobile collection end and client end of playing back, comprehensive adaptive decision-making.
Form traditional client server mode in the present invention between mobile collection end, client end of playing back and adaptation services device, realize communicating by letter between client-server by socket.Adopt RTP and User Datagram Protoco (UDP) transmitting video data between mobile collection end and client end of playing back.After client end of playing back is initiated video request to the mobile collection end, the mobile collection end is started working, and gathers video data and according to default Transmit Bit Rate value, video flowing is sent to client end of playing back, for the user, is watched.The adaptation services device is started working simultaneously, monitors the real time data information from mobile collection end and client end of playing back at the port of appointment, and carries out adaptive decision-making according to these information, and the workflow diagram of adaptation services device is shown in Fig. 3.
Below carry out detailed description for adaptation algorithm, algorithm flow can be with reference to figure 4.The adaptation algorithm parameter of the inventive method comprises that mobile collection end network signal intensity Ws, client end of playing back network signal intensity Wc, mobile collection end send video type CT, the client user experiences 4 parameters of QoE scoring MOS.
Concrete adaptation algorithm is as follows: first the network signal intensity Wc of mobile collection end network signal intensity Ws and client end of playing back is divided into to some grades according to its span, as S1, S2, S3, S4,5 ranks of S5, the corresponding signal strength signal intensity interval of each rank reduces successively from S1 to S5; Again the Transmit Bit Rate SBR of mobile collection end is carried out to corresponding classification, as A, B, C, D, 5 ranks of E, the corresponding Transmit Bit Rate interval of each rank, from A to E, reduce successively, then judge according to the occurrence of the network signal intensity Wc of current mobile collection end network signal intensity Ws and client end of playing back the rank that it is corresponding, and mapping out its corresponding Transmit Bit Rate SBR rank according to table 1, table 1 is as follows.
table 1, the network signal intensity that in table, Ws is the mobile collection end, the network signal intensity that Wc is client end of playing back, SBR means Transmit Bit Rate.
After determining the rank of Transmit Bit Rate SBR, next static according to the Type C T(of current transmission of video again, microinching, rapid movement) and the user experience the occurrence that QoE scoring MOS determines Transmit Bit Rate.
Specific practice is as follows: using the minimum value in other speed interval at the corresponding levels as base value SBR
l, can suppose a Transmit Bit Rate value △ SBR of unit (being determined by corresponding speed rank), for experiencing the QoE scoring, video type and user set corresponding coefficient k and m.For transmission of video Type C T, its corresponding coefficient value k is arranged, as the video pictures for static, microinching, rapid movement, its video coefficients k can get 0,1,2 successively; And experience QoE scoring MOS value for the user of user feedback, itself and previous user are experienced to the QoE scoring to be compared: if descend to some extent, take family and experience the Coefficient m of QoE scoring=1, expression should improve video quality, the transmission rate of decision-making can be increased to a unit value; Otherwise take family and experience the Coefficient m of QoE scoring=0.Final adaptive comprehensive transmission rate should be SBR=SBR
l+ k △ SBR+m △ SBR, after drawing best transmission rate, the adaptation services device is sent to the mobile collection end by the transmission rate value after decision-making, carries out the adjustment of real-time video Transmit Bit Rate.
Client end of playing back is when watching real-time video, can be given a mark to the quality of current video, be that the user experiences the QoE scoring, and this scoring is fed back to adaptation services device end, adaptation services device end is judged according to this value, if the threshold value that this scoring is experienced the QoE scoring lower than minimum user triggers at once adaptation algorithm and adjusts current video Transmit Bit Rate, in order to adjust in time the video quality of transmission, otherwise using this scoring as the reference value of Adaptive Rate Shape next time.
This method medium-rate needs the situation of self adaptation adjustment to have two kinds: 1, when the network signal intensity of mobile collection end and client end of playing back changes, and, during the rank change of the Transmit Bit Rate of its mapping, now will trigger the adjustment of the Transmit Bit Rate of mobile collection end; 2, the user when user feedback experiences the QoE scoring lower than default minimum threshold, will trigger adaptation algorithm, carries out in time the speed adjustment.Adopt this mode can carry out in due course the self adaptation adjustment of transmission rate, and reduced unnecessary adjustment, and considered fully user's subjective feeling, thereby can provide more comfortable experience for the user.
Claims (5)
1. a real-time video transmission speed self-adaption method of experiencing based on the user, be based on the network architecture consisted of mobile collection end, client end of playing back and adaptation services device three parts, and its feature comprises the following steps:
A) adaptation services device initialization, monitored at the port of appointment, prepares to receive the real time data information from mobile collection end and client end of playing back;
B) mobile collection end initialization, start to monitor self network condition and moving state, and network strength (Ws), transmission video type (CT) information exchange are crossed to socket communication and be sent to the adaptation services device; The client end of playing back initialization, start to monitor self network condition, and network strength (Wc) information is sent to the adaptation services device;
C) client end of playing back is initiated the transmission of video request to the mobile collection end, starts to transmit real time video data between the two; The adaptation services device is opened adaptation services, experience scoring (MOS) according to network signal intensity (Ws), transmission of video type (CT), the network signal intensity (Wc) of client end of playing back and the user of user feedback of current mobile collection end, by the adaptation algorithm decision-making, go out to be applicable to the best Transmit Bit Rate (SBR) of the present situation and be sent to the mobile collection end;
D) after the mobile collection termination is received, Transmit Bit Rate is adjusted into to described best Transmit Bit Rate (SBR) value, the video data that client end of playing back receives after adjusting is watched.
2. a kind of real-time video transmission speed self-adaption method of experiencing based on the user according to claim 1 is characterized in that:
Transmit Bit Rate adaptation module in described mobile collection end is used for receiving the Transmit Bit Rate value of adaptation algorithm decision-making, and the Transmit Bit Rate of mobile collection end is adjusted into to this value;
Network condition monitoring modular in described mobile collection end and client end of playing back for the transmission of video process to mobile collection end and client end of playing back separately the signal strength signal intensity of residing network monitored, and network signal intensity value separately is sent to the adaptation services device;
Transmission of video type identification module in described mobile collection end is used for judging the type of sports of mobile collection end transmission of video, and sends it to the parameter of adaptation services device as adaptation algorithm;
User in described client end of playing back experiences (QoE) grading module and video quality is given a mark in the process of watching video for the user, and this value is fed back to the adaptation services device to carry out adaptation services;
Adaptive decision-making module in described adaptation services device is responsible for receiving the every data message from mobile collection end and client end of playing back, comprehensive adaptive decision-making.
3. a kind of real-time video transmission speed self-adaption method of experiencing based on the user according to claim 1, it is characterized in that, form traditional client server mode between described mobile collection end, client end of playing back and adaptation services device, realize communicating by letter between client-server by socket.
4. a kind of real-time video transmission speed self-adaption method of experiencing based on the user according to claim 1, it is characterized in that, the parameter of described adaptation algorithm comprises mobile collection end network signal intensity (Ws), client end of playing back network signal intensity (Wc), mobile collection end transmission of video type (CT), client active user experience scoring (MOS) 4 parameters;
Concrete adaptation algorithm: first the network signal intensity of mobile collection end and client end of playing back is divided into to 5 ranks according to its span; Again Transmit Bit Rate (SBR) correspondingly is divided into to 5 ranks, then according to the occurrence of the network signal intensity of current mobile collection end and client end of playing back, judges the rank that it is corresponding, and map out its corresponding Transmit Bit Rate rank; After determining the rank of Transmit Bit Rate (SBR), then experience according to current transmission video type and user the occurrence that Transmit Bit Rate is determined in scoring.
5. a kind of real-time video transmission speed self-adaption method of experiencing based on the user according to claim 1, it is characterized in that, it is that client end of playing back is when watching real-time video that described user experiences scoring, can be given a mark to the quality of current video, and this scoring is fed back to adaptation services device end, if the threshold value of scoring is experienced in this scoring lower than minimum user, trigger at once adaptation algorithm and adjust current video Transmit Bit Rate, otherwise this user is experienced to scoring as the parameter value of Adaptive Rate Shape next time.
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