CN1487451A - Flow media search system in teleteaching domain based on MPEG-7 - Google Patents
Flow media search system in teleteaching domain based on MPEG-7 Download PDFInfo
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Abstract
The present invention belongs to the field of multimedia application technology. The flow media search system in teleteaching domain based on MPEG-7 has characteristic extracting/storing end and flow media intermediate, the characteristic extracting and storing end is connected to the flow media intermediate via calling ADO data base and RTP/RTSP flow media transmission protocol, and the flow media intermediate is connected to client end via RTP/RTSP flow media transmission protocol and TCP/IP network. The characteristic extracting/creating/storing end completes the automatic characteristic extraction and the manual labeling; and the flow media intermediate converts the inquiry of the client end into the XQuery syntax inquiry to XML data base. The client end provides the users with convenient multimode inquiry interface, records user's information and sends the inquiry request and personal file to the flow media intermediate.
Description
Technical field
The present invention relates to the Streaming Media searching system in a kind of remote teaching field, particularly a kind of Streaming Media searching system of the remote teaching field based on MPEG-7 (Chinese technical term is " Multimedia Content Description Interface ") belongs to the multimedia application technical field.
Background technology
Development of Multimedia Technology causes available multi-medium data rapid growth at present.Yet how becoming a generally acknowledged difficult problem from these content of multimedia the inside extraction Useful Informations systems that also structure is practical, maximum obstruction is to lack simple, a understandable and extendible multimedia descriptions to be used for constructing efficiently, easily to expand and telescopic multimedia application.As: through looking into new discovery, U.S. Patent number US2003103675, patent name " Multimediainformation retrieval method; program; record medium and system (method of multimedia information retrieval, program, record media and system) ", in this patent document, the inventor has proposed a kind of image and textual description to be paired into the thought of one " message unit ", the retrieval that is converted into for multimedia retrieval text.It proposes the notion of " Virtual Space " to come cluster according to the weights and the frequency of text the inside word, and the function of similarity multimedia inquiry is provided.Also find in the retrieval, U.S. Patent number US2003033318, patent name " Instantly indexed databases for multimedia content analysis andretrieval (instant multimedia content analysis, retrieval and database index) ", in this patent document, the inventor has proposed a kind of the real-time event of real world (such as goal of football match) Real time identification and deposit multimedia database in for browsing and retrieve.It cooperates association area knowledge by the analysis of sensor, generates the event description data in real time.There is following problem in this system: do not support the retrieval of the Streaming Media in long-distance education field; Do not meet international standard; System's portability is not strong.
Summary of the invention
The objective of the invention is to defective or deficiency at the prior art existence, a kind of Streaming Media searching system of the remote teaching field based on MPEG-7 is provided, make its Streaming Media of supporting remote teaching field retrieval, meet the MPEG-7 international standard, for an excellent environment is created in remote teaching.
The present invention is achieved by the following technical solutions, the Streaming Media searching system in the remote teaching field based on MPEG-7 of the present invention is by feature extraction/storage end, Streaming Media middleware and client are formed, feature extraction/storage end transmits agreement by ADO data base call and RTP/RTSP Streaming Media and links to each other with the Streaming Media middleware, and the Streaming Media middleware transmits agreement by the RTP/RTSP Streaming Media and the TCP/IP network links to each other with client.Feature extraction/storage end is responsible for the Automatic Extraction/manual mark of feature, uses self-defining MPEG-7 description scheme to generate standard format, deposits the XML database then in.The Streaming Media middleware is between feature extraction/storage end and client, the search request of client is converted into inquiry to the XQuery grammer of XML database, from the XML database of feature extraction/storage end, obtain corresponding results, and, feed back to client through after optimizing.The multi-mode query interface that client is provided convenience is given the user, and personalized information such as the query history of recording user and hobby, and query requests and Profile are sent to the Streaming Media middleware.
1, feature extraction/storage end
Feature extraction/storage end comprises the Streaming Media source, three parts of Streaming Media feature extraction/labeling module and Streaming Media feature description database are formed, the Streaming Media source links to each other with Streaming Media feature extraction/labeling module by the TCP/IP network, and Streaming Media feature extraction/labeling module links to each other with Streaming Media feature description database by ADO teledata library call.The Streaming Media source comprises live and two the part compositions of streaming media on demand of real time flow medium, provides and wants processed stream medium data.Streaming Media feature description database is an XML database, is used for preserving the Streaming Media feature description data of generation.Streaming Media feature extraction/labeling module is between Streaming Media source and Streaming Media feature description database, it is the core of feature extraction/storage end, it accepts the live or some broadcasting flow-medium data of coming in the Streaming Media source, through automatic or manual handle, generation meets the Streaming Media feature description of mark, deposits in the Streaming Media feature description database.Streaming Media feature extraction/labeling module comprises the MPEG-7 description scheme towards long-distance education, automated characterization extracts and manual three parts of mark of describing are formed, and wherein the MPEG-7 description scheme towards long-distance education has defined the automated characterization extraction and manually described the required common mode of following of mark.
2, Streaming Media middleware
The Streaming Media middleware is by metadata search engine, three parts of personalized search/browse recommended engine and video transformation coding engine are formed, metadata search engine links to each other with personalized search/browse recommended engine by the communication between process, and personalized search/browse recommended engine links to each other with the transform coding engine by the TCP/IP network.Metadata search engine links to each other with Streaming Media feature description database by the XQuery query interface, metadata search engine is inquired about corresponding information by the XQuery query interface from Streaming Media feature description database after receiving the searching request of client/browse selection.Give personalized search/browse recommended engine the result who inquires then; Personalized search/browse recommended engine obtains user profile, individual character hobby, search history record from client, thus the generation final search result/browse recommendation results to give the video transformation coding engine; The video transformation coding engine produces the stream medium data of different resolution, different bit rates and different coding demoder to corresponding client terminal device according to the difference of client terminal device.
3, client
Client is supported multiple terminal device, can be PC and various handheld device.It selects module and user profile, individual character hobby, search history recording module two parts to form by user search request/browse, user search request/browse and select module to link to each other with user profile, individual character hobby, search history recording module by the system journal record, user profile wherein, the individual character hobby, the search history recording module has write down the each searching request of user automatically and has browsed selection, and provides the configuration page to allow the client import some individual character hobbies.
The present invention has substantive distinguishing features and marked improvement, the present invention meets international standard, Streaming Media retrieval at education sector, real-time and non real-time feature extraction are combined, low layer and high-level characteristic combine, have intelligence, efficient, unified and scalability, mobile device can pass through the wireless network self-adaptation easily, abundant multimedia resource is freely searched for, visited on personalized ground.
Description of drawings
Fig. 1 is a system architecture synoptic diagram of the present invention
Fig. 2 is Streaming Media feature extraction of the present invention/labeling module structural representation
Fig. 3 is a metadata search engine of the present invention working mechanism synoptic diagram
Fig. 4 video transformation coding engine of the present invention working mechanism synoptic diagram.
Embodiment
For a more clear understanding of the present invention, below in conjunction with accompanying drawing technical scheme of the present invention is described in further detail.As shown in the figure, the Streaming Media searching system that the present invention is based on the remote teaching field of MPEG-7 is held by feature extraction/storage, Streaming Media middleware and client are formed, feature extraction/storage end transmits agreement by ADO data base call and RTP/RTSP Streaming Media and links to each other with the Streaming Media middleware, and the Streaming Media middleware transmits agreement by the RTP/RTSP Streaming Media and the TCP/IP network links to each other with client.Feature extraction/generation/storage end is responsible for the Automatic Extraction/manual mark of feature, uses self-defining MPEG-7 description scheme to generate standard format, deposits the XML database then in.The Streaming Media middleware is between feature extraction/storage end and client, the search request of client is converted into inquiry to the XQuery grammer of XML database, from the XML database of feature extraction/storage end, obtain corresponding results, and, feed back to client through after optimizing.The multi-mode query interface that client is provided convenience is given the user, and personalized information such as the query history of recording user and hobby, and query requests and Profile are sent to the Streaming Media middleware.
Be that feature extraction/storage end, Streaming Media middleware and client are further described to each subsystem of the present invention respectively below.
1, feature extraction/storage end
As shown in Figure 1, feature extraction/storage end comprises the Streaming Media source, three parts of Streaming Media feature extraction/mark and Streaming Media feature description database are formed, the Streaming Media source links to each other with Streaming Media feature extraction/labeling module by the TCP/IP network, and Streaming Media feature extraction/labeling module links to each other with Streaming Media feature description database by ADO teledata library call.The Streaming Media source comprises live and two the part compositions of streaming media on demand of real time flow medium, provides and wants processed stream medium data.Streaming Media feature description database is an XML database, is used for preserving the Streaming Media feature description data of generation.Streaming Media feature extraction/labeling module is between Streaming Media source and Streaming Media feature description database, it is the core of feature extraction/storage end, it accepts the live or some broadcasting flow-medium data of coming in the Streaming Media source, through automatic or manual handle, generation meets the Streaming Media feature description of mark, deposits in the Streaming Media feature description database.
As shown in Figure 2, Streaming Media feature extraction/labeling module comprises automatically description and non real-time editing specification two parts in real time:
(1) automatically in real time describe part: it is cut apart with automatic marking system two parts by video flowing and forms.Wherein video flowing is cut apart module real-time video-voice frequency flow and screen teaching data flow point is slit into camera lens one by one.Automatically labeling module is formed by cutting apart the camera lens, ppt lecture notes, semantic dictionary and automatic annotation tool four parts that obtain.Semantic dictionary comprises 3 parts: static scene, key object and incident, annotation tool calls semantic dictionary and describes these camera lenses automatically, and the text in the Automatic Extraction PPT lecture notes carries out the semantic description of contextual analysis as synchronous camera lens.After finishing on the class, its preliminary video semanteme summary (comprising semantic description and feature description) has also just generated automatically like this.
(2) non real-time editing specification part: it is cut apart with semi-automatic labeling system two parts by video flowing and forms.Wherein video flowing is cut apart module video-voice frequency flow and screen teaching data flow point is slit into camera lens one by one.Semi-automatic labeling system is formed by cutting apart the camera lens, semantic dictionary, mark people and semi-automatic annotation tool four parts that obtain.Semantic dictionary comprises 3 parts: static scene, key object and incident, the mark people uses semi-automatic annotation tool manually to add, revise and delete all marks for these camera lenses.
2, Streaming Media middleware
As shown in Figure 1, the Streaming Media middleware is by metadata search engine, three parts of personalized search/browse recommended engine and video transformation coding engine are formed, metadata search engine links to each other with personalized search/browse recommended engine by the communication between process, and personalized search/browse recommended engine links to each other with the transform coding engine by the TCP/IP network.Metadata search engine links to each other with Streaming Media feature description database by the XQuery query interface, metadata search engine is after receiving the searching request of client/browse selection, from Streaming Media feature description database, inquire about corresponding information by the XQuery query interface, give personalized search/browse recommended engine the result who inquires then; Personalized search/browse recommended engine obtains user profile from client, the individual character hobby, and the search history record, thus the generation final search result/browse recommendation results to give the video transformation coding engine; The video transformation coding engine produces different resolution according to client terminal device, different bit rates, and the stream medium data of different coding demoder is given corresponding client terminal device.
As shown in Figure 3, metadata search engine is the core of Streaming Media middleware, metadata search engine is one low layer multimedia feature such as color, shape and texture and high-level semantic feature is combined to determine a feedback search engine of weights, and uses feedback algorithm to come the optimization searching result.All MPEG-7 describe and leave among the primary XML database Tamino, and this database provides the powerful XQuery query language that is similar to SQL that is exclusively used in XML document.Handling the description that inquires through the MPEG-7 interpreter after, the MPEG-7 database carries out the similarity search of physics low-level feature and high-level semantic feature respectively, and use relevant feedback algorithm optimization Search Results, in video database, find corresponding video data to represent to the user visually with form easily then through the video transformation coding engine.
As shown in Figure 4, the video transformation coding engine is made up of original video stream decoder module, MPEG4 recodification module and MPEG-7 transform coding prompting parameter configuration instrument three parts.The original video stream decoder module was not compressed the video stream data of original code check by corresponding decoder decode video stream data; The extendible hierarchical coding algorithm of the adaptive MPEG-4 scrambler of MPEG4 recodification module service property (quality) recompile, the video flowing of the code check that obtains recoding; MPEG-7 transform coding prompting parameter configuration instrument, the motion prompting parameter that it extracts from existing video file, difficulty prompting parameter and importance prompting parameter are automatically adjusted or the manual configuration parameter.The MPEG-7 transform coding that the video transformation coding engine generates according to the parameter configuration instrument is pointed out content of multimedia is handled accordingly.
3, client
As shown in Figure 1, client is supported different terminal devices, comprise PC and various handheld device, it selects module and user profile by user search request/browse, the individual character hobby, search history recording module two parts are formed, user search request/browse and select module by the system journal record with producing configuration file, the individual character hobby, the search history recording module links to each other, user profile wherein, the individual character hobby, the search history recording module has write down each searching request of user automatically and has browsed selection, and provides the configuration page to allow the client import some individual character hobbies.
Claims (8)
1, a kind of Streaming Media searching system of the remote teaching field based on MPEG-7, form by Streaming Media middleware and client, it is characterized in that also comprising: feature extraction/storage end, feature extraction/storage end transmits agreement by ADO data base call and RTP/RTSP Streaming Media and links to each other with the Streaming Media middleware, the Streaming Media middleware transmits agreement by the RTP/RTSP Streaming Media and the TCP/IP network links to each other with client, feature extraction/generation/storage end is responsible for the Automatic Extraction/manual mark of feature, use self-defining MPEG-7 description scheme to generate standard format, deposit the XML database then in, the Streaming Media middleware is between feature extraction/storage end and client, the search request of client is converted into inquiry to the XQuery grammer of XML database, from the XML database of feature extraction/storage end, obtain corresponding results, and after optimizing, feed back to client, the multi-mode query interface that client is provided convenience is given the user, and the information that the query history of recording user and hobby etc. are personalized sends to the Streaming Media middleware to query requests and Profile.
2, the Streaming Media searching system in the remote teaching field based on MPEG-7 according to claim 1, it is characterized in that, feature extraction/storage end comprises the Streaming Media source, three parts of Streaming Media feature extraction/labeling module and Streaming Media feature description database are formed, the Streaming Media source links to each other with Streaming Media feature extraction/labeling module by the TCP/IP network, Streaming Media feature extraction/labeling module links to each other with Streaming Media feature description database by ADO teledata library call, Streaming Media feature extraction/labeling module is between Streaming Media source and Streaming Media feature description database, it is the core of feature extraction/storage end, it accepts the live or some broadcasting flow-medium data of coming in the Streaming Media source, processing through Streaming Media feature extraction/labeling module, generation meets the Streaming Media feature description of mark, deposits in the Streaming Media feature description database.
3, the Streaming Media searching system in the remote teaching field based on MPEG-7 according to claim 2 is characterized in that, Streaming Media feature extraction/labeling module comprises to be described and non real-time editing specification two parts automatically in real time:
(1) automatically in real time describe part: it is cut apart with automatic marking system two parts by video flowing and forms, wherein video flowing is cut apart module real-time video-voice frequency flow and screen teaching data flow point is slit into camera lens one by one, automatically labeling module is by cutting apart the camera lens that obtains, the ppt lecture notes, semantic dictionary and automatic annotation tool four parts are formed, semantic dictionary comprises 3 parts: static scene, key object and incident, automatically annotation tool calls semantic dictionary and describes these camera lenses, and the text in the Automatic Extraction PPT lecture notes carries out the semantic description of contextual analysis as synchronous camera lens, after intact on the class, its preliminary video semanteme summary has just generated automatically;
(2) non real-time editing specification part: it is cut apart with semi-automatic labeling system two parts by video flowing and forms, wherein video flowing is cut apart module video-voice frequency flow and screen teaching data flow point is slit into camera lens one by one, semi-automatic labeling system is formed by cutting apart the camera lens, semantic dictionary, mark people and semi-automatic annotation tool four parts that obtain, semantic dictionary comprises 3 parts: static scene, key object and incident, mark go into to use semi-automatic annotation tool manually to add, revise and delete all marks for these camera lenses.
4, the Streaming Media searching system in the remote teaching field based on MPEG-7 according to claim 1, it is characterized in that, the Streaming Media source comprises live and two the part compositions of streaming media on demand of real time flow medium, provide and want processed stream medium data, Streaming Media feature description database is an XML database, be used for preserving the Streaming Media feature description data of generation, Streaming Media feature extraction/labeling module comprises the MPEG-7 description scheme towards long-distance education, automated characterization extracts and manual three parts of mark of describing are formed, and wherein the MPEG-7 description scheme towards long-distance education has defined the automated characterization extraction and manually described the required common mode of following of mark.
5, the Streaming Media searching system in the remote teaching field based on MPEG-7 according to claim 1, it is characterized in that, the Streaming Media middleware is by metadata search engine, three parts of personalized search/browse recommended engine and video transformation coding engine are formed, metadata search engine links to each other with the search/browse recommended engine of personalization by the communication between process, personalized search/browse recommended engine links to each other with the transform coding engine by the TCP/IP network, metadata search engine links to each other with Streaming Media feature description database by the XQuery query interface, metadata search engine is after receiving the searching request of client/browse selection, from Streaming Media feature description database, inquire about corresponding information by the XQuery query interface, give personalized search/browse recommended engine the result who inquires then, personalized search/browse recommended engine obtains user profile from client, the individual character hobby, the search history record, thereby generation final search result/browse recommendation results to give the video transformation coding engine, the video transformation coding engine produces corresponding resolution according to client terminal device, the stream medium data of bit rate and coding decoder is given corresponding client terminal device.
6, the Streaming Media searching system in the remote teaching field based on MPEG-7 according to claim 5, it is characterized in that, metadata search engine is one low layer multimedia feature such as color, shape and texture and high-level semantic feature is combined to determine a feedback search engine of weights, and uses feedback algorithm to come the optimization searching result.
7, the Streaming Media searching system in the remote teaching field based on MPEG-7 according to claim 5, it is characterized in that, the video transformation coding engine is by the original video stream decoder module, MPEG4 recodification module and MPEG-7 transform coding prompting parameter configuration instrument three parts are formed, the original video stream decoder module was not compressed the video stream data of original code check by corresponding decoder decode video stream data, the extendible hierarchical coding algorithm of the adaptive MPEG-4 scrambler of MPEG4 recodification module service property (quality) recompile, the video flowing of code check obtains recoding, MPEG-7 transform coding prompting parameter configuration instrument, the motion prompting parameter that it extracts from existing video file, difficulty prompting parameter and importance prompting parameter, automatically adjust or the manual configuration parameter, the MPEG-7 transform coding that the video transformation coding engine generates according to the parameter configuration instrument is pointed out content of multimedia is handled accordingly.
8, the Streaming Media searching system in the remote teaching field based on MPEG-7 according to claim 1, it is characterized in that, client is supported multiple terminal device, it selects module and user profile by user search request/browse, the individual character hobby, search history recording module two parts are formed, user search request/browse and select module by system journal record and user profile, the individual character hobby, the search history recording module links to each other, user profile wherein, the individual character hobby, the search history recording module has write down each searching request of user automatically and has browsed selection, and provides the configuration page to allow the client import some individual character hobbies.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN104603740A (en) * | 2012-08-08 | 2015-05-06 | 亚马逊技术股份有限公司 | Archival data identification |
| CN104750858A (en) * | 2015-04-16 | 2015-07-01 | 成都影泰科技有限公司 | Network-based data storage method |
| US9563681B1 (en) | 2012-08-08 | 2017-02-07 | Amazon Technologies, Inc. | Archival data flow management |
| US9652487B1 (en) | 2012-08-08 | 2017-05-16 | Amazon Technologies, Inc. | Programmable checksum calculations on data storage devices |
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| CN111818278A (en) * | 2020-07-17 | 2020-10-23 | 济南浪潮高新科技投资发展有限公司 | Teaching video acquisition and retrieval system and method |
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- 2003-08-12 CN CN 03142208 patent/CN1266635C/en not_active Expired - Fee Related
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| US9779035B1 (en) | 2012-08-08 | 2017-10-03 | Amazon Technologies, Inc. | Log-based data storage on sequentially written media |
| US9563681B1 (en) | 2012-08-08 | 2017-02-07 | Amazon Technologies, Inc. | Archival data flow management |
| US9652487B1 (en) | 2012-08-08 | 2017-05-16 | Amazon Technologies, Inc. | Programmable checksum calculations on data storage devices |
| CN104603740A (en) * | 2012-08-08 | 2015-05-06 | 亚马逊技术股份有限公司 | Archival data identification |
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| US9830111B1 (en) | 2012-08-08 | 2017-11-28 | Amazon Technologies, Inc. | Data storage space management |
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| US10698880B2 (en) | 2012-08-08 | 2020-06-30 | Amazon Technologies, Inc. | Data storage application programming interface |
| US10558581B1 (en) | 2013-02-19 | 2020-02-11 | Amazon Technologies, Inc. | Systems and techniques for data recovery in a keymapless data storage system |
| CN104750858A (en) * | 2015-04-16 | 2015-07-01 | 成都影泰科技有限公司 | Network-based data storage method |
| US11386060B1 (en) | 2015-09-23 | 2022-07-12 | Amazon Technologies, Inc. | Techniques for verifiably processing data in distributed computing systems |
| CN111818278A (en) * | 2020-07-17 | 2020-10-23 | 济南浪潮高新科技投资发展有限公司 | Teaching video acquisition and retrieval system and method |
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