CN112073807B - Video data processing method and device based on block chain - Google Patents

Video data processing method and device based on block chain Download PDF

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CN112073807B
CN112073807B CN202011253429.3A CN202011253429A CN112073807B CN 112073807 B CN112073807 B CN 112073807B CN 202011253429 A CN202011253429 A CN 202011253429A CN 112073807 B CN112073807 B CN 112073807B
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target key
video object
material video
video
blockchain
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CN112073807A (en
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徐惠
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Alipay Hangzhou Information Technology Co Ltd
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Alipay Hangzhou Information Technology Co Ltd
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    • 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, rendering scenes according to MPEG-4 scene graphs
    • H04N21/44008—Processing of video elementary streams, e.g. splicing a video clip retrieved from local storage with an incoming video stream, rendering scenes according to MPEG-4 scene graphs involving operations for analysing video streams, e.g. detecting features or characteristics in the video stream
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/70—Information retrieval; Database structures therefor; File system structures therefor of video data
    • G06F16/78—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
    • G06F16/783—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
    • G06F16/7834—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content using audio features
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/70—Information retrieval; Database structures therefor; File system structures therefor of video data
    • G06F16/78—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
    • G06F16/783—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
    • G06F16/7837—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content using objects detected or recognised in the video content
    • G06F16/784—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content using objects detected or recognised in the video content the detected or recognised objects being people
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/70—Information retrieval; Database structures therefor; File system structures therefor of video data
    • G06F16/78—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
    • G06F16/7867—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using information manually generated, e.g. tags, keywords, comments, title and artist information, manually generated time, location and usage information, user ratings
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/60—Protecting data
    • G06F21/64—Protecting data integrity, e.g. using checksums, certificates or signatures
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G06Q40/04—Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange
    • 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, rendering scenes according to MPEG-4 scene graphs
    • H04N21/44012—Processing of video elementary streams, e.g. splicing a video clip retrieved from local storage with an incoming video stream, rendering scenes according to MPEG-4 scene graphs involving rendering scenes according to scene graphs, e.g. MPEG-4 scene graphs
    • 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]
    • H04N21/80—Generation or processing of content or additional data by content creator independently of the distribution process; Content per se
    • H04N21/83—Generation or processing of protective or descriptive data associated with content; Content structuring
    • H04N21/835—Generation of protective data, e.g. certificates
    • H04N21/8358—Generation of protective data, e.g. certificates involving watermark

Abstract

The present specification provides a method and an apparatus for processing video data based on a block chain, including: calling a preset video segmentation program to segment a source video into a plurality of material video objects; generating a target key corresponding to the material video object based on the position information of the key frame image contained in the material video object and the copyright information of the source video; and after the target key is sent to the block chain for storing the certificate, adding watermark information to the material video object based on the target key or the block chain certificate storing identification of the target key.

Description

Video data processing method and device based on block chain
Technical Field
One or more embodiments of the present disclosure relate to the field of blockchain technologies, and in particular, to a method and an apparatus for processing video data based on a blockchain.
Background
The block chain technology, also called distributed ledger technology, is an emerging technology in which several computing devices participate in "accounting" together, and a complete distributed database is maintained together. The blockchain technology has been widely used in many fields due to its characteristics of decentralization, transparency, participation of each computing device in database records, and rapid data synchronization between computing devices.
Copyright infringement is frequent when the video industry based on the internet is developed and prosperous. At present, the main infringement forms include content transportation, such as second theft, code printing, picture-in-picture and the like, secondary creation, namely unauthorized, editing of original materials for secondary creation, reference of video materials (some platforms or individuals split the works into a plurality of segments to provide for the public without permission of others), and the like.
Disclosure of Invention
In view of this, one or more embodiments of the present specification provide a method for processing video data based on a block chain, including:
calling a preset video segmentation program to segment a source video into a plurality of material video objects;
generating a target key corresponding to the material video object based on the position information of the key frame image contained in the material video object and the copyright information of the source video;
and after the target key is sent to the block chain for storing the certificate, adding watermark information to the material video object based on the target key or the block chain certificate storing identification of the target key.
In another illustrated embodiment, the invoking a preset video segmentation program to segment the source video into a plurality of material video objects includes:
acquiring facial features of a plurality of designated persons;
and identifying images containing each designated person from the source video based on a face recognition algorithm by taking the facial features of the persons as reference, and generating the images containing each designated person as a material video object of the designated person.
In another illustrated embodiment, the invoking a preset video segmentation program to segment the source video into a plurality of material video objects includes:
performing voice recognition and semantic analysis on the audio information of the source video, segmenting the audio information of the source video, and establishing scene labels for segmented audio segments;
acquiring a designated scene of a material video object to be generated;
and generating a material video object of the specified scene corresponding to the audio clip based on the audio clip corresponding to the scene label matched with the specified scene.
In another illustrated embodiment, the invoking a preset video segmentation program to segment the source video into a plurality of material video objects includes:
and based on a preset video semantic recognition algorithm, dividing the source video into a plurality of material video objects containing a plurality of specified scenes.
In yet another illustrated embodiment, the copyright information of the source video is copyright information validated via the blockchain authentication.
In another illustrated embodiment, the adding watermark information to the material video object based on the target key or the blockchain certification mark of the target key includes:
generating a watermark picture based on the target key or the block chain certificate storage identification of the target key;
and adding the watermark picture into the key frame image contained in the material video object.
In another illustrated embodiment, the adding watermark information to the material video object based on the target key or the blockchain certification mark of the target key includes:
and adding blind watermark information to the material video object based on the target key or the evidence storing identification of the target key by adopting a blind watermark algorithm.
In still another illustrated embodiment, the generating a target key corresponding to the material video object based on the position information of the key frame image included in the material video object and the copyright information of the source video includes:
respectively taking each frame image contained in the material video object as a key frame image, and respectively generating a target key corresponding to each frame image of the material video object based on the position information of each key frame image in the material video object and the copyright information of the source video;
generating a watermark picture based on the target key or the block chain certificate of the target key, and adding the watermark picture to the key frame image contained in the material video object;
respectively generating watermark pictures corresponding to each frame of image based on the target key corresponding to each frame of image or the block chain certificate storage identification of the target key corresponding to each frame of image;
and adding the watermark picture distribution corresponding to each frame of image into each frame of image contained in the material video object.
In yet another illustrated embodiment, a smart contract for forensic management of the target key is deployed in the blockchain; the method comprises the following steps of generating a target key corresponding to a material video object based on copyright information of the material video object, and issuing the target key to a block chain for evidence storage, wherein the steps comprise:
constructing a first invocation transaction for the smart contract based at least on the copyright information of the material video object;
issuing the first call transaction to the blockchain to cause node devices of the blockchain to call the smart contract in response to the received first call transaction, execute key generation and certification logic declared by the smart contract, generate a target key for a material video object based on at least copyright information of the material video object, and store the target key or a blockchain certification identity of the target key in the blockchain.
In still another illustrated embodiment, the copyright information of the material video object included in the first call transaction is copyright information in an encrypted state.
Accordingly, the present specification also provides a device for processing video data based on a block chain, including:
the segmentation unit is used for calling a preset video segmentation program and segmenting a source video into a plurality of material video objects;
a generation unit that generates a target key corresponding to the material video object based on position information of a key frame image contained in the material video object and copyright information of the source video;
and the adding unit is used for adding watermark information to the material video object based on the target key or the block chain certificate storage identification of the target key after the target key is sent to the block chain for certificate storage.
In yet another illustrated embodiment, the segmentation unit is further configured to:
acquiring facial features of a plurality of designated persons;
and identifying images containing each designated person from the source video based on a face recognition algorithm by taking the facial features of the persons as reference, and generating the images containing each designated person as a material video object of the designated person.
In yet another illustrated embodiment, the segmentation unit is further configured to:
performing voice recognition and semantic analysis on the audio information of the source video, segmenting the audio information of the source video, and establishing scene labels for segmented audio segments;
acquiring a designated scene of a material video object to be generated;
and generating a material video object of the specified scene corresponding to the audio clip based on the audio clip corresponding to the scene label matched with the specified scene.
In yet another illustrated embodiment, the segmentation unit is further configured to:
and based on a preset video semantic recognition algorithm, dividing the source video into a plurality of material video objects containing a plurality of specified scenes.
In yet another illustrated embodiment, the copyright information of the source video is copyright information validated via the blockchain authentication.
In yet another illustrated embodiment, the adding unit is further configured to:
generating a watermark picture based on the target key or the block chain certificate storage identification of the target key;
and adding the watermark picture into the key frame image contained in the material video object.
In yet another illustrated embodiment, the generating unit is further configured to:
respectively taking each frame image contained in the material video object as a key frame image, and respectively generating a target key corresponding to each frame image of the material video object based on the position information of each key frame image in the material video object and the copyright information of the source video;
the adding unit is further configured to:
respectively generating watermark pictures corresponding to each frame of image based on the target key corresponding to each frame of image or the block chain certificate storage identification of the target key corresponding to each frame of image;
and adding the watermark picture distribution corresponding to each frame of image into each frame of image contained in the material video object.
In yet another illustrated embodiment, the adding unit is further configured to:
and adding blind watermark information to the material video object based on the target key or the evidence storing identification of the target key by adopting a blind watermark algorithm.
In yet another illustrated embodiment, a smart contract for forensic management of the target key is deployed in the blockchain; the method comprises the following steps of generating a target key corresponding to a material video object based on copyright information of the material video object, and issuing the target key to a block chain for evidence storage, wherein the steps comprise:
constructing a first invocation transaction for the smart contract based at least on the copyright information of the material video object;
issuing the first call transaction to the blockchain to cause node devices of the blockchain to call the smart contract in response to the received first call transaction, execute key generation and certification logic declared by the smart contract, generate a target key for a material video object based on at least copyright information of the material video object, and store the target key or a blockchain certification identity of the target key in the blockchain.
In still another illustrated embodiment, the copyright information of the material video object included in the first call transaction is copyright information in an encrypted state.
Accordingly, this specification also proposes a computer device comprising: a memory and a processor; the memory having stored thereon a computer program executable by the processor; the processor executes the computer program to perform the processing method of video data based on a block chain according to the embodiments.
Compared with a source video, a material video object belongs to a video object which is easier to be stolen by an illegal infringer, and according to the processing method and the processing device for video data based on the block chain, provided by the embodiments of the specification, after the source video is cut into the material video object, watermark information is added to the material video object; therefore, the method avoids the problem that more computer resources are consumed due to larger source video when the source video is subjected to watermarking processing, and also carries out watermarking processing on the target works by using the target key after the certification is stored on the block chain or the block chain certification storage identification of the target key, so that the block chain certification storage is carried out on the copyright information of the material video object by using the anti-tampering mechanism of the block chain, and the block chain certification is convenient to carry out when the material video object is maliciously stolen by a copyright thief.
Drawings
FIG. 1 is a schematic diagram of creating an intelligent contract provided by an exemplary embodiment;
FIG. 2 is a schematic diagram of invoking an intelligent contract, provided by an exemplary embodiment;
FIG. 3 is a schematic diagram of creating an intelligent contract and invoking an intelligent contract provided by an exemplary embodiment;
fig. 4 is a flowchart illustrating a method for processing video data based on a blockchain according to an exemplary embodiment;
fig. 5 is a schematic diagram of an apparatus for processing video data based on a blockchain according to an exemplary embodiment;
fig. 6 is a hardware configuration diagram for operating an embodiment of the data processing apparatus or the copyrighted-information verification apparatus provided in the present specification.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with one or more embodiments of the present specification.
It should be noted that: in other embodiments, the steps of the corresponding methods are not necessarily performed in the order shown and described herein. In some other embodiments, the method may include more or fewer steps than those described herein. Moreover, a single step described in this specification may be broken down into multiple steps for description in other embodiments; multiple steps described in this specification may be combined into a single step in other embodiments.
With the unprecedented prosperity and development of the internet-based video dissemination and application industry, however, copyright infringement behaviors are frequent when the industry develops prosperities. At present, the main infringement forms comprise content transportation, such as second stealing, code printing, picture-in-picture and the like, secondary creation, namely unauthorized editing, secondary creation of original materials, reference of video materials (certain platforms or individuals split the works into a plurality of segments to provide for the public without permission of others), and victims comprise short videos, movie and television shows and also comprise works such as comprehensive sports music cartoons and the like. And the infringement use of the scene material video in the long video becomes a disaster area, and the reasonable use of the video material is urgently required to be standardized.
In view of the above problems, one or more embodiments of the present specification provide a processing method for video data based on a blockchain, which provides technical support for source tracing and source proof after a video is infringed, so that a video originator can prove right affiliation of the video based on a proof of existence identifier on the blockchain after the video is infringed.
The block chain or block chain network described in one or more embodiments of the present specification may specifically refer to a P2P network system having a distributed data storage structure, where each node device achieves through a common recognition mechanism, the book data in the block chain is distributed within temporally consecutive "blocks", and the latter block may include a data digest of the former block, and according to a difference of a specific common recognition mechanism (such as POW, POS, DPOS, PBFT, or the like), a full backup of data of all or part of nodes is achieved.
Blockchains are generally divided into three types: public chain (Public Blockchain), Private chain (Private Blockchain) and alliance chain (Consortium Blockchain). Furthermore, there may be a combination of the above types, such as private chain + federation chain, federation chain + public chain, and so on.
Among them, the most decentralized is the public chain. The public chain is represented by bitcoin and ether house, and participants (also called nodes in the block chain) joining the public chain can read data records on the chain, participate in transactions, compete for accounting rights of new blocks, and the like. Moreover, each node can freely join or leave the network and perform related operations.
Private chains are the opposite, with the network's write rights controlled by an organization or organization and the data read rights specified by the organization. Briefly, a private chain may be a weakly centralized system with strict restrictions on nodes and a small number of nodes. This type of blockchain is more suitable for use within a particular establishment.
A federation chain is a block chain between a public chain and a private chain, and "partial decentralization" can be achieved. Each node in a federation chain typically has a physical organization or organization corresponding to it; the nodes are authorized to join the network and form a benefit-related alliance, and block chain operation is maintained together.
The computing device may construct the data into a standard transaction (transaction) format supported by the blockchain, then issue the transaction to the blockchain, perform consensus processing on the received transaction by the node devices in the blockchain, and package the transaction into a block by the node devices serving as accounting nodes in the blockchain after the consensus is achieved, and perform persistent evidence storage in the blockchain.
Regardless of which consensus algorithm is adopted by the block chain, the accounting node can pack the received transaction to generate a latest block and send the latest block to other node devices for consensus verification. If the latest block is received by other node equipment and no problem is proved, the latest block can be added to the tail of the original block chain, so that the accounting process of the block chain is completed. The transactions contained in the block may also be performed during the process of the other nodes verifying the new block sent by the accounting node.
It should be noted that, each time a latest block is generated in the blockchain, the corresponding status of the executed transactions in the blockchain changes after the transaction in the latest block is executed. For example, in a block chain constructed by an account model, the account status of an external account or a smart contract account usually changes correspondingly with the execution of a transaction.
For example, when a "transfer transaction" is completed in a block, the balances of the transferring party account and the transferring party account associated with the "transfer transaction" (i.e., the field values of the Balance fields of these accounts) are usually changed.
For another example, the "intelligent contract invocation transaction" in the block is used to invoke an intelligent contract deployed on the blockchain, invoke the intelligent contract in the EVM corresponding to the node device to execute the "intelligent contract invocation transaction", and update the account status of the intelligent contract account in the account of the intelligent contract after the execution of the intelligent contract invocation transaction.
In practical applications, whether public, private, or alliance, it is possible to provide the functionality of a Smart contract (Smart contract). An intelligent contract on a blockchain is a contract on a blockchain that can be executed triggered by a transaction. An intelligent contract may be defined in the form of code.
Taking an Etherhouse as an example, a user is supported to create and call some complex logic in the Etherhouse network. The ethernet workshop is used as a programmable block chain, and the core of the ethernet workshop is an ethernet workshop virtual machine (EVM), and each ethernet workshop node can run the EVM. The EVM is a well-behaved virtual machine through which various complex logic can be implemented. The user issuing and invoking smart contracts in the etherhouse is running on the EVM. In fact, the EVM directly runs virtual machine code (virtual machine bytecode, hereinafter referred to as "bytecode"), so the intelligent contract deployed on the blockchain may be bytecode.
After Bob sends a Transaction (Transaction) containing information to create a smart contract to the ethernet network, each node can execute the Transaction in the EVM, as shown in fig. 1. The From field of the transaction in the figure is used for recording the address of the account initiating the creation of the intelligent contract, the contract code stored in the field value of the Data field of the transaction can be byte code, and the field value of the To field of the transaction is a null account. After the nodes reach the agreement through the consensus mechanism, the intelligent contract is successfully created, and the follow-up user can call the intelligent contract.
After the intelligent contract is established, a contract account corresponding to the intelligent contract appears on the block chain, and the block chain has a specific address; for example, "0 x68e12cf284 …" in each node in fig. 1 represents the address of the contract account created; the contract Code (Code) and account store (Storage) will be maintained in the account store for that contract account. The behavior of the intelligent contract is controlled by the contract code, while the account storage of the intelligent contract preserves the state of the contract. In other words, the intelligent contract causes a virtual account to be generated on the blockchain that contains the contract code and account storage.
As mentioned above, the Data field containing the transaction that created the intelligent contract may hold the byte code of the intelligent contract. A bytecode consists of a series of bytes, each of which can identify an operation. Based on the multiple considerations of development efficiency, readability and the like, a developer can select a high-level language to write intelligent contract codes instead of directly writing byte codes. For example, the high-level language may employ a language such as Solidity, Serpent, LLL, and the like. For intelligent contract code written in a high-level language, the intelligent contract code can be compiled by a compiler to generate byte codes which can be deployed on a blockchain.
Taking the Solidity language as an example, the contract code written by it is very similar to a Class (Class) in the object-oriented programming language, and various members including state variables, functions, function modifiers, events, etc. can be declared in one contract. A state variable is a value permanently stored in an account Storage (Storage) field of an intelligent contract to save the state of the contract.
As shown in FIG. 2, still taking the Etherhouse as an example, after Bob sends a transaction containing the information of the calling intelligent contract to the Etherhouse network, each node can execute the transaction in the EVM. The From field of the transaction in the figure is used for recording the address of the account initiating the intelligent contract calling, the To field is used for recording the address of the intelligent contract called, and the Data field of the transaction is used for recording the method and the parameters for calling the intelligent contract. After invoking the smart contract, the account status of the contract account may change. Subsequently, a client may check the account status of the contract account through the accessed block link points, for example, the account status may be stored in the Storage tree of the intelligent contract in the form of a Key-Value pair. The results of the execution of the transaction that invokes the smart contract, which may be in the form of a transaction receipt (receipt), are stored in the MPT receipt tree.
The intelligent contract can be independently executed at each node in the blockchain network in a specified mode, and execution records and data are stored in the blockchain, so that after the transaction is executed, transaction certificates which cannot be tampered and cannot be lost are stored in the blockchain.
A schematic diagram of creating an intelligent contract and invoking the intelligent contract is shown in fig. 3. An intelligent contract is created in an Ethernet workshop and needs to be subjected to the processes of compiling the intelligent contract, changing the intelligent contract into byte codes, deploying the intelligent contract to a block chain and the like. The intelligent contract is called in the Ethernet workshop, a transaction pointing to the intelligent contract address is initiated, the EVM of each node can respectively execute the transaction, and the intelligent contract code is distributed and operated in the virtual machine of each node in the Ethernet workshop network.
For accounts in a blockchain, the account status of the account is usually maintained through a structure. When a transaction in a block is executed, the status of the account associated with the transaction in the block chain is also typically changed.
Taking etherhouses as an example, the structure of an account usually includes fields such as Balance, Nonce, Code and Storage. Wherein:
a Balance field for maintaining the current account Balance of the account;
a Nonce field for maintaining a number of transactions for the account; the counter is used for guaranteeing that each transaction can be processed only once, and replay attack is effectively avoided;
a Code field for maintaining a contract Code for the account; in practical applications, only the hash value of the contract Code is typically maintained in the Code field; thus, the Code field is also commonly referred to as the Codhash field.
A Storage field for maintaining the Storage contents of the account (default field value is null); for a contract account, a separate storage space is usually allocated to store the storage content of the contract account; this separate storage space is often referred to as the account storage of the contract account. The storage content of the contract account is usually constructed into a data structure of an MPT (media Patricia Trie) tree and stored in the independent storage space; in which, the Storage content based on the contract account is constructed into an MPT tree, which is also commonly referred to as a Storage tree. Whereas the Storage field typically maintains only the root node of the Storage tree; thus, the Storage field is also commonly referred to as the Storage root field.
Wherein, for the external account, the field values of the Code field and the Storage field shown above are both null values.
For most blockchain models, Merkle trees are typically used; alternatively, the data is stored and maintained based on the data structure of the Merkle tree. Taking etherhouses as an example, the etherhouses use MPT tree (a Merkle tree variation) as a data organization form for organizing and managing important data such as account status, transaction information, and the like.
The Etherhouse designs three MPT trees, namely an MPT state tree, an MPT transaction tree and an MPT receipt tree, aiming at data needing to be stored and maintained in a block chain. In addition to the three MPT trees, there is actually a Storage tree constructed based on the Storage content of the contract account.
An MPT state tree, which is an MPT tree organized by account state data of all accounts in a blockchain; an MPT transaction tree, which is an MPT tree organized by transaction (transaction) data in a blockchain; the MPT receipt tree is organized into transaction (receipt) receipts corresponding to each transaction generated after the transactions in the block are executed. The hash values of the root nodes of the MPT state tree, the MPT transaction tree, and the MPT receipt tree shown above are eventually added to the block header of the corresponding block.
The MPT transaction tree and the MPT receipt tree correspond to the blocks, namely each block has the MPT transaction tree and the MPT receipt tree. For the MPT transaction tree, the MPT receipt tree and the MPT state tree which are organized, the MPT transaction tree, the MPT receipt tree and the MPT state tree are finally stored in a Key-Value type database (such as a levelDB) which adopts a multi-level data storage structure.
Based on the above-mentioned blockchain technology basis, as shown in fig. 4, an exemplary embodiment shown in this specification provides a processing method of video data based on blockchain, which is executed by a computing device having a direct or indirect connection relationship with a blockchain network. When the computing device is directly connected to the blockchain network, the computing device may be a client or a node device of the blockchain; when a computing device is indirectly connected to the blockchain network, the computing device may be communicatively connected to a client or node device of the blockchain.
In one or more embodiments provided in this specification, the client may be an independent device connected to any node device of the blockchain, or may be a functional module disposed inside any node device, which is not limited herein.
Fig. 4 illustrates a processing method of video data based on a block chain according to an exemplary embodiment of the present specification, where the method is executed by the above-mentioned computing device, and includes:
step 402, a preset video segmentation program is called to segment the source video into a plurality of material video objects.
The source video can comprise a long video of an episode such as a movie, an animation and the like, or a long video recorded by an original author. The method for segmenting the source video into the plurality of material video objects can comprise manual segmentation or calling an AI video segmentation program interface to perform corresponding video segmentation operation.
For example, when video contents of a plurality of persons are contained in a source video, the above-described computing apparatus may call an AI video segmentation program interface that can generate a designated person video, thereby segmenting the source video into a plurality of material video objects each containing the designated person.
The specific process of source video segmentation can include:
specifying, via a user, a facial image of person A, B, C in an image contained in the source video, or inputting, by a user, a facial image of person A, B, C, to cause the computing device to obtain facial features of specified person A, B, C;
an AI video segmentation program interface that can generate a designated person video is called, the persons are tracked and recognized based on a face recognition algorithm with the facial features of the person A, B, C as a reference, an image containing each designated person is obtained from the source video by recognition, and the image containing each designated person is generated as material video objects of the designated person, that is, three material video objects containing the person a, the person B, and the person C, respectively, are generated.
Optionally, the AI video segmentation program is invoked, and the human body contour and the background in the three material video objects including the person a, the person B, and the person C can be separated, so as to obtain three material video objects including only the person a, the person B, and the person C, thereby facilitating further creation of the material video objects.
For another example, when the source video is a scenario-like video work such as a movie or a tv show, the computing device may further divide the source video into a plurality of material video objects based on the scenario or scene of the source video. At this time, the specific process of source video segmentation may include:
calling an AI scene video segmentation program interface, carrying out voice recognition and semantic analysis on the audio information of the source video, segmenting the audio information of the source video, and establishing a scene label for the segmented audio clip; for example, by performing voice recognition and semantic analysis on the audio information of the source video, audio segments such as quarrel, dining, running and the like are segmented from the audio information of the source video, and scene tags are established for the audio segments;
acquiring a designated scene of a material video object to be generated; for example, a user inputs a specified "quarrel" scene to the computing device through a human-computer interaction interface of the computing device;
and generating a material video object of the specified scene corresponding to the audio fragment based on the audio fragment corresponding to the scene label matched with the specified scene, namely the noise frame.
For some source video works with insufficient audio information, the computing device may further segment the source video into a plurality of material video objects including a plurality of designated scenes by calling a preset video semantic recognition program interface. The segmentation process may generally include image recognition → image feature extraction and label creation → video segmentation according to the features required by the user, and the like, which is not described herein again.
Those skilled in the art can develop various video segmentation programs to segment the source video into the material video objects suitable for various requirements based on actual requirements, which is not limited in the present embodiment.
Step 404, generating a target key corresponding to the material video object based on at least the copyright information of the source video.
The copyright information of the source video may include author information and authoring time information of the source video.
In order to further ensure the authenticity and validity of the copyright information of the source video, in another embodiment, the copyright information of the source video is valid copyright information authenticated by the blockchain.
The specific way of authenticating the copyright information by the blockchain can be set according to specific requirements. For example, the blockchain may set an intelligent contract for copyright registration of a work, and a node device of the blockchain may store identification information (e.g., a hash digest) of the source video and copyright information of the source video in the blockchain by calling the intelligent contract for copyright registration of the work; at this time, the copyright information successfully stored in the block chain is the copyright information authenticated by the block chain.
For another example, the method for processing video data based on a block chain further includes:
performing infringement verification on the source video on the blockchain;
and when the source video is an infringed original work, recording copyright information of the source video into the block chain to determine the right of the source video. In this embodiment, when the source video is an infringed original work, the copyright information of the source video is recorded in the block chain, where the copyright information is effective copyright information authenticated by the block chain.
The embodiment is not limited to the specific process of performing infringement verification on the source video on the block chain, and those skilled in the art can develop various infringement verification intelligent contracts so as to perform a verification process of whether to infringe the copyright of the existing video works or not based on the characteristic information of the source video. For example, a hash comparison method is adopted to verify whether the hash abstract of the source video is the same as the hash abstract of the existing video work, so as to verify whether the source video is the original work; for another example, a vector similarity meter algorithm of the video images is adopted to calculate whether the vector distance between the vector of the video image contained in the obtained source video and the vector of the video image contained in the existing video work is greater than a preset threshold value, and if so, the source video can be judged to be the original work; and so on.
After the copyright information of the source video is acquired, the computing device can generate a target key corresponding to the material video object based on the copyright information of the source video by using a preset key generation algorithm. The target key may include a plaintext of the copyright information, or in order to protect privacy and security of the copyright information, the target key may include a ciphertext obtained by performing encryption calculation on the copyright information, or include a hash digest of the copyright information, and the like, which is not limited in this specification.
In order to further increase the association between the content of the material video object and the target key, in a further illustrated embodiment, the target key of the material video object may be generated based on the position information of the key frame image included in the material video object and the copyright information of the source video. The position information may include time axis information of the key frame image in the material video object. The present embodiment is not limited to the manner of acquiring the key frame image, and the computing device executing the data processing may randomly select one frame image from the target video as the key frame. At this time, according to a preset key generation algorithm, a key generation operation is performed on the copyright information of the target work, the position information of the key frame image included in the target video, and a key generation parameter (for example, a random code corresponding to the key frame), so as to generate a target key corresponding to the target video.
In still another illustrated embodiment, the target key of the material video object may be generated based on position information of a key frame image included in the material video object and copyright information of the source video; the position information includes time axis information of the key frame image in the source video in addition to time axis information of the key frame image in the material video object. Therefore, the material video object and the source video are associated through the target key, and the credibility of the copyright information of the material video object is further enhanced in the infringement and testification stage.
The skilled person can also start from the actual certificate storage requirement or the parameter requirement of the key generation algorithm, add other content information or algorithm parameters that need to be stored when generating the target key in addition to the above-mentioned copyright information, and generate the target key based on the preset key generation algorithm and the content information or algorithm parameters and the above-mentioned copyright information.
Step 406, after the target key is sent to the block chain for certification storage, adding watermark information to the material video object based on the target key or the block chain certification storage identifier of the target key.
In an embodiment, when the computing device generating the target key serves as a client of the blockchain, the certifying the target key on the blockchain includes: and constructing a key certificate transaction based on the target key, and sending the key certificate transaction to the block chain for storage. The blockchain certificate ID of the target key may include a transaction ID (TxID) of the key certificate transaction or a hash digest of the target key.
In another embodiment, when the computing device generating the target key is a computing device connected to a client of the blockchain, the verifying the target key on the blockchain includes: and sending the target key to a client or node equipment of the block chain, constructing and packaging the target key into key evidence storage transaction by the client or node equipment of the block chain, and sending the evidence storage transaction to the block chain for evidence storage. The blockchain certificate ID of the target key may include a transaction ID (TxID) of the key certificate transaction or a hash digest of the target key.
In yet another illustrated embodiment, when the computing device is used as a client of a blockchain or is connected to a client of a blockchain, the process of generating a target key corresponding to the material video object based on at least the copyright information of the source video and storing the target key on the blockchain may also be implemented by invoking, by a node device, a smart contract for performing storage management on the target key, where the smart contract is deployed on the blockchain.
Specifically, the computing device may construct a first invocation transaction for the smart contract based at least on the copyright information of the source video; or the computing device may send the copyright information of the source video to the client of the blockchain, so that the client of the blockchain constructs a first invocation transaction for the intelligent contract based on the copyright information of the source video;
issuing the first call transaction to the blockchain to cause node devices of the blockchain to call the smart contract in response to the received first call transaction, execute key generation and validation logic of the smart contract statement, and generate a target key for the material video object based on at least copyright information of the source video; after the first invocation transaction or the execution result of the first invocation transaction (including the target key) is identified by the blockchain, the target key or the certificate identifier of the target key can be stored in the blockchain.
In order to further protect the privacy and security of the copyright information of the target work, the copyright information included in the first invoking transaction may be in an encrypted state. The blockchain certificate identifier of the target key may include a hash digest of the target key, or a transaction ID (TXID) of the first call transaction, or a retrieval identifier generated by the smart contract for the target key, so that the node device may retrieve the target key in a blockchain (e.g., an account storage space of the smart contract) through the blockchain certificate identifier of the target key.
According to the key generation logic stated by the smart contract, when the target key is generated and the position information of the key frame is also needed, the first call transaction also comprises the position information of the key frame in the video material object, or the position information of the key frame in the source video.
The adding of the watermark information to the material video object based on the target key or the block chain voucher id of the target key in this embodiment may include generating the target key or the block chain voucher id of the target key into a watermark picture, and adding the watermark picture to each frame image of the material video object; or adding the watermark picture to a plurality of frame images selected from the material video object. In order to prevent illegal infringers from editing and cutting the material video object and then discarding the image segments containing the watermark images, the image which is displayed by the material video object and is related to key support can be selected for carrying out watermarking processing.
In still another embodiment, the image subjected to the watermarking process may include the key frame image described in each of the above embodiments. When the target key is generated based on the copyright information of the source video and the position information of the key frame, the watermark picture is added into the key frame, and the relevance between the target key and the key frame position can be increased, so that when the material video object is illegally stolen, the key frame position corresponding to the plain text of the target key can be obtained based on the target key indicated by the watermark picture extracted from a certain frame in the stolen video segment or the block chain certification mark of the target key, the key frame at the key frame position contained in the material video object is compared with the certain frame in the stolen video segment, and if the images are consistent, the stolen video segment can be proved to be taken from the material video object.
In this embodiment, in order to prevent the video segment that is stolen by the video embezzler from not containing the watermark picture, the computing device may add a watermark picture to each frame of image contained in the material video object: specifically, the target key corresponding to the position of each frame of image may be generated based on the position of each frame of image included in the material video object and the copyright information of the source video, respectively; and respectively generating the target key or the block chain certificate identification of the target key into watermark pictures, and correspondingly adding the watermark pictures to each frame of image corresponding to the positions. In this way, the copyright information based on the source video and the watermark image information generated at the position of each frame image are added to each frame image of the material video object, so that the probability that the stolen image of the material video object contains the watermark information when the material video object is stolen is improved.
The watermarking processing technology is not specifically limited in the embodiment, and a person skilled in the art can disassemble the material video object and add the watermark information related to the position of each frame image to the material video object one by one; and integrally processing the material video object based on a preset watermarking algorithm to obtain the material video object with each frame image added with the watermarking information corresponding to the position of the frame image.
The obvious watermark superposition technology is easier to detect by video infringers, so that the infringers can easily crack the copyright defense of the original works by adopting the modes of watermark cutting, watermark shielding and the like.
Therefore, in a further illustrated embodiment, the above computing device may perform watermarking processing by using a blind watermarking algorithm, and in particular, the above watermarking information for the material video object based on the target key or the blockchain certification mark of the target key includes:
performing two-dimensional Fourier transform on an image to be added with a watermark to obtain a frequency domain image;
generating the target key or the block chain certificate storage identification of the target key into an original watermark picture;
taking a random code, generating a disorder rule, and disordering the pixels of the original watermark picture according to the disorder rule; performing two-dimensional Fourier transform on the disturbed watermark picture, and superposing the disturbed watermark picture on a frequency domain picture obtained by the transformation according to a preset superposition intensity coefficient;
and performing two-dimensional inverse Fourier transform on the frequency domain graph containing the watermark, which is obtained by superposition, to obtain an image containing the blind watermark.
The target work processed based on the blind watermarking algorithm has no perception at the front end, so that the alertness of a pirate is reduced, and the probability of removing the watermark by a video pirate is reduced.
It should be noted that the random code for generating the out-of-order rule may also be used to generate the target key, that is, the target key is generated based on the copyright information of the source video, the position information of the key frame, and the random code; and after the target key is stored in the block chain, carrying out blind watermarking by using a random code for generating a target object to be stored. Therefore, when the image to be added with the watermark information is the key frame, block chain storage is indirectly carried out on the random code parameters involved in the blind watermark processing process, blind watermark extraction is conveniently carried out on the computing equipment based on the real and effective random codes, and execution efficiency of blind watermark information extraction is improved; the method can further prove the true validity of copyright information of the source video which generates the target key together with the random code when the blind watermark extraction is successful.
After watermarking processing is carried out on a material video object obtained by carrying out video segmentation processing on the basis of a source video, the computing equipment can also generate a content label for the material video object according to the content of the material video object and correspondingly store the content label and the material video object added with watermarking information, so that the management of the material object is facilitated, and secondary creation of the content is facilitated by selecting a proper material video object on the basis of the content label of the material video object.
In the method for processing video data based on a block chain provided in one or more embodiments, a target key generated based on copyright information of a source video is stored on the block chain, and a block chain storage identifier of the target key or the target key is used to perform watermarking on a video material object divided from the source video.
Corresponding to the above flow implementation, the embodiment of the present specification further provides a processing apparatus 50 for video data based on a block chain. The apparatus 50 may be implemented by software, or by hardware, or by a combination of hardware and software. Taking a software implementation as an example, the logical device is formed by reading a corresponding computer program instruction into a memory for running through a Central Processing Unit (CPU) of the device. In terms of hardware, the device in which the apparatus is located generally includes other hardware such as a chip for transmitting and receiving wireless signals and/or other hardware such as a board for implementing a network communication function, in addition to the CPU, the memory, and the storage shown in fig. 6.
As shown in fig. 5, the present specification further provides a device 50 for processing video data based on a block chain, including:
a dividing unit 502, which invokes a preset video dividing program to divide the source video into a plurality of material video objects;
a generating unit 504 that generates a target key corresponding to the material video object based on position information of a key frame image included in the material video object and copyright information of the source video;
and an adding unit 506, configured to add watermark information to the material video object based on the target key or the block chain certification storage identifier of the target key after sending the target key to the block chain for certification storage.
In yet another illustrated embodiment, the dividing unit 502 is further configured to:
acquiring facial features of a plurality of designated persons;
and identifying images containing each designated person from the source video based on a face recognition algorithm by taking the facial features of the persons as reference, and generating the images containing each designated person as a material video object of the designated person.
In yet another illustrated embodiment, the dividing unit 502 is further configured to:
performing voice recognition and semantic analysis on the audio information of the source video, segmenting the audio information of the source video, and establishing scene labels for segmented audio segments;
acquiring a designated scene of a material video object to be generated;
and generating a material video object of the specified scene corresponding to the audio clip based on the audio clip corresponding to the scene label matched with the specified scene.
In yet another illustrated embodiment, the dividing unit 502 is further configured to:
and based on a preset video semantic recognition algorithm, dividing the source video into a plurality of material video objects containing a plurality of specified scenes.
In yet another illustrated embodiment, the copyright information of the source video is copyright information validated via the blockchain authentication.
In yet another illustrated embodiment, the adding unit 506 is further configured to:
generating a watermark picture based on the target key or the block chain certificate storage identification of the target key;
and adding the watermark picture into the key frame image contained in the material video object.
In yet another illustrated embodiment, the adding unit 506 is further configured to:
and adding blind watermark information to the material video object based on the target key or the evidence storing identification of the target key by adopting a blind watermark algorithm.
In yet another illustrated embodiment, the generating unit 504 is further configured to:
respectively taking each frame image contained in the material video object as a key frame image, and respectively generating a target key corresponding to each frame image of the material video object based on the position information of each key frame image in the material video object and the copyright information of the source video;
the adding unit 506 is further configured to:
respectively generating watermark pictures corresponding to each frame of image based on the target key corresponding to each frame of image or the block chain certificate storage identification of the target key corresponding to each frame of image;
and adding the watermark picture distribution corresponding to each frame of image into each frame of image contained in the material video object.
In yet another illustrated embodiment, a smart contract for forensic management of the target key is deployed in the blockchain; the method comprises the following steps of generating a target key corresponding to a material video object based on copyright information of the material video object, and issuing the target key to a block chain for evidence storage, wherein the steps comprise:
constructing a first invocation transaction for the smart contract based at least on the copyright information of the material video object;
issuing the first call transaction to the blockchain to cause node devices of the blockchain to call the smart contract in response to the received first call transaction, execute key generation and certification logic declared by the smart contract, generate a target key for a material video object based on at least copyright information of the material video object, and store the target key or a blockchain certification identity of the target key in the blockchain.
In still another illustrated embodiment, the copyright information of the material video object included in the first call transaction is copyright information in an encrypted state.
The implementation process of the functions and actions of each unit in the apparatus 50 is specifically described in the implementation process of the corresponding step in the above processing method of video data based on a block chain, and related points may be referred to the partial description of the method embodiment, and are not described herein again.
The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical modules, may be located in one place, or may be distributed on a plurality of network modules. Some or all of the units or modules can be selected according to actual needs to achieve the purpose of the solution in the specification. One of ordinary skill in the art can understand and implement it without inventive effort.
The apparatuses, units and modules illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product with certain functions. A typical implementation device is a computer, which may take the form of a personal computer, laptop computer, cellular telephone, camera phone, smart phone, personal digital assistant, media player, navigation device, email messaging device, game console, tablet computer, wearable device, or a combination of any of these devices.
Corresponding to the above method embodiments, embodiments of the present specification further provide a computer device, as shown in fig. 6, including a memory and a processor. Wherein the memory has stored thereon a computer program executable by the processor; the processor, when executing the stored computer program, performs the steps of the method for processing video data based on a blockchain in the embodiments of the present specification. For a detailed description of each step of the above processing method for video data based on a block chain, please refer to the previous contents, which is not repeated.
The above description is only a preferred embodiment of the present disclosure, and should not be taken as limiting the present disclosure, and any modifications, equivalents, improvements, etc. made within the spirit and principle of the present disclosure should be included in the scope of the present disclosure.
In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data.
Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
As will be appreciated by one skilled in the art, embodiments of the present description may be provided as a method, system, or computer program product. Accordingly, embodiments of the present description may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, embodiments of the present description may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and so forth) having computer-usable program code embodied therein.

Claims (21)

1. A method for processing video data based on a blockchain, comprising:
calling a preset video segmentation program to segment a source video into a plurality of material video objects;
generating a target key corresponding to the material video object based on the position information of the key frame image contained in the material video object and the copyright information of the source video;
and after the target key is sent to the block chain for storing the certificate, adding watermark information to the material video object based on the target key or the block chain certificate storing identification of the target key.
2. The method of claim 1, wherein said invoking a preset video segmentation routine to segment the source video into a plurality of material video objects comprises:
acquiring facial features of a plurality of designated persons;
and identifying images containing each designated person from the source video based on a face recognition algorithm by taking the facial features of the persons as reference, and generating the images containing each designated person as a material video object of the designated person.
3. The method of claim 1, wherein said invoking a preset video segmentation routine to segment the source video into a plurality of material video objects comprises:
performing voice recognition and semantic analysis on the audio information of the source video, segmenting the audio information of the source video, and establishing scene labels for segmented audio segments;
acquiring a designated scene of a material video object to be generated;
and generating a material video object of the specified scene corresponding to the audio clip based on the audio clip corresponding to the scene label matched with the specified scene.
4. The method of claim 1, wherein said invoking a preset video segmentation routine to segment the source video into a plurality of material video objects comprises:
and based on a preset video semantic recognition algorithm, dividing the source video into a plurality of material video objects containing a plurality of specified scenes.
5. The method of claim 1, wherein the copyright information of the source video is copyright information validated via the blockchain authentication.
6. The method of claim 1, wherein adding watermark information to the material video object based on the target key or the blockchain certification mark of the target key comprises:
generating a watermark picture based on the target key or the block chain certificate storage identification of the target key;
and adding the watermark picture into the key frame image contained in the material video object.
7. The method according to claim 6, wherein the generating of the target key corresponding to the material video object based on the position information of the key frame image contained in the material video object and the copyright information of the source video comprises:
respectively taking each frame image contained in the material video object as a key frame image, and respectively generating a target key corresponding to each frame image of the material video object based on the position information of each key frame image in the material video object and the copyright information of the source video;
generating a watermark picture based on the target key or the block chain certificate of the target key, and adding the watermark picture to the key frame image contained in the material video object;
respectively generating watermark pictures corresponding to each frame of image based on the target key corresponding to each frame of image or the block chain certificate storage identification of the target key corresponding to each frame of image;
and respectively adding the watermark picture corresponding to each frame of image into each frame of image contained in the material video object.
8. The method of claim 1, wherein adding watermark information to the material video object based on the target key or the blockchain certification mark of the target key comprises:
and adding blind watermark information to the material video object based on the target key or the evidence storing identification of the target key by adopting a blind watermark algorithm.
9. The method of claim 1, the blockchain having disposed therein a smart contract for forensic management of the target key; generating a target key corresponding to the material video object based on the position information of the key frame image contained in the material video object and the copyright information of the source video; and issuing the target key to a blockchain for evidence storage, wherein the process comprises the following steps:
constructing a first call transaction to the smart contract based on at least copyright information of the material video object and position information of a key frame image contained in the material video object;
issuing the first call transaction to the blockchain to cause node devices of the blockchain to call the smart contract in response to the received first call transaction, execute key generation and certification logic declared by the smart contract, generate a target key corresponding to the material video object based on the position information of the key frame image and the copyright information of the source video, and store the target key or a blockchain certification mark of the target key in the blockchain.
10. The method of claim 9, wherein the copyright information of the material video object included in the first call transaction is copyright information in an encrypted state.
11. An apparatus for processing video data based on a blockchain, comprising:
the segmentation unit is used for calling a preset video segmentation program and segmenting a source video into a plurality of material video objects;
a generation unit that generates a target key corresponding to the material video object based on position information of a key frame image contained in the material video object and copyright information of the source video;
and the adding unit is used for adding watermark information to the material video object based on the target key or the block chain certificate storage identification of the target key after the target key is sent to the block chain for certificate storage.
12. The apparatus of claim 11, the segmentation unit, further to:
acquiring facial features of a plurality of designated persons;
and identifying images containing each designated person from the source video based on a face recognition algorithm by taking the facial features of the persons as reference, and generating the images containing each designated person as a material video object of the designated person.
13. The apparatus of claim 11, the segmentation unit, further to:
performing voice recognition and semantic analysis on the audio information of the source video, segmenting the audio information of the source video, and establishing scene labels for segmented audio segments;
acquiring a designated scene of a material video object to be generated;
and generating a material video object of the specified scene corresponding to the audio clip based on the audio clip corresponding to the scene label matched with the specified scene.
14. The apparatus of claim 11, the segmentation unit, further to:
and based on a preset video semantic recognition algorithm, dividing the source video into a plurality of material video objects containing a plurality of specified scenes.
15. The device of claim 11, copyright information of the source video is copyright information that is validated via the blockchain authentication.
16. The apparatus of claim 11, the adding unit, further configured to:
generating a watermark picture based on the target key or the block chain certificate storage identification of the target key;
and adding the watermark picture into the key frame image contained in the material video object.
17. The apparatus of claim 16, the generating unit further to:
respectively taking each frame image contained in the material video object as a key frame image, and respectively generating a target key corresponding to each frame image of the material video object based on the position information of each key frame image in the material video object and the copyright information of the source video;
the adding unit is further configured to:
respectively generating watermark pictures corresponding to each frame of image based on the target key corresponding to each frame of image or the block chain certificate storage identification of the target key corresponding to each frame of image;
and respectively adding the watermark picture corresponding to each frame of image into each frame of image contained in the material video object.
18. The apparatus of claim 11, the adding unit, further configured to:
and adding blind watermark information to the material video object based on the target key or the evidence storing identification of the target key by adopting a blind watermark algorithm.
19. The apparatus of claim 11, the blockchain having disposed therein a smart contract for forensic management of the target key; generating a target key corresponding to the material video object based on the position information of the key frame image contained in the material video object and the copyright information of the source video; and issuing the target key to a blockchain for evidence storage, wherein the process comprises the following steps:
constructing a first call transaction to the smart contract based on at least copyright information of the material video object and position information of a key frame image contained in the material video object;
issuing the first call transaction to the blockchain to cause node devices of the blockchain to call the smart contract in response to the received first call transaction, execute key generation and certification logic declared by the smart contract, generate a target key corresponding to the material video object based on the position information of the key frame image and the copyright information of the source video, and store the target key or a blockchain certification mark of the target key in the blockchain.
20. The apparatus of claim 19, wherein the copyright information of the material video object included in the first call transaction is copyright information in an encrypted state.
21. A computer device, comprising: a memory and a processor; the memory having stored thereon a computer program executable by the processor; the processor, when executing the computer program, performs the method of any of claims 1 to 10.
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