Feature value transfer-based data flow processing method and related apparatus

Abstract

Embodiments of the present application disclose a data stream processing method based on feature value transfer and a related device, which can be applied to various scenes such as cloud technology, artificial intelligence, intelligent transportation, etc. When the recording service of a target Internet of Things terminal is started, a target feature value transfer event is completed for a target object, and the target Internet of Things terminal synchronously acquires target image data stream corresponding to the target feature value transfer event. The target image data stream includes a plurality of ordered target images, and records the target feature value transfer event. The target image data stream is associated with a target event identifier corresponding to the target feature value transfer event, a target data stream file is generated and stored, and the target data stream file can trace the target feature value transfer event. The target data stream file is sent to a server, so that the server stores the target data stream file. In the case of payment disputes due to misidentification or malicious identification, the target feature value transfer event can be traced back, and the payment disputes can be conveniently supported and handled.

Description

Technical Field

[0001] This application relates to the field of data processing, and in particular to a data stream processing method and related apparatus based on eigenvalue transfer. Background Technology

[0002] With the development of the Internet of Things (IoT), electronic payments can be realized based on IoT terminals. When shopping, users do not need to carry or use their own smart devices; they can complete electronic payments directly at the IoT terminals provided by merchants. For example, electronic payments can be completed through facial recognition at the IoT terminals provided by merchants.

[0003] However, the aforementioned electronic payment methods based on facial recognition can lead to payment disputes in cases of misidentification or malicious identification. Since these methods primarily focus on how to perform facial recognition to make electronic payments, they are insufficient to address the aforementioned payment disputes. Summary of the Invention

[0004] To address the aforementioned technical issues, this application provides a data stream processing method and related apparatus based on feature value transfer. In the event of a payment dispute due to misidentification or malicious identification, the target feature value transfer event can be traced, thereby facilitating the handling of the payment dispute.

[0005] The embodiments of this application disclose the following technical solutions:

[0006] On the one hand, this application provides a data stream processing method based on eigenvalue transfer, the method comprising:

[0007] If the recording service of the target IoT terminal is enabled, a target feature value transfer event is completed for the target object, and the target image data stream corresponding to the target feature value transfer event is acquired synchronously. The target image data stream includes multiple ordered target images.

[0008] Based on the target image data stream and the target event identifier corresponding to the target feature value transfer event, a target data stream file is generated and stored, and the target data stream file is used to trace the target feature value transfer event;

[0009] The target data stream file is sent to the server.

[0010] On the other hand, this application provides a data stream processing method based on eigenvalue transfer, the method comprising:

[0011] The system receives a target data stream file sent by a target IoT terminal. The target data stream file is generated based on the target image data stream and target event identifier corresponding to the target feature value transfer event completed by the target object. The target data stream file is used to trace the target feature value transfer event. The target image data stream includes multiple ordered target images.

[0012] Store the target data stream file.

[0013] On the other hand, this application provides a data stream processing apparatus based on eigenvalue transfer, the apparatus comprising: an acquisition unit, a generation unit, and a transmission unit;

[0014] The acquisition unit is used to acquire the target image data stream corresponding to the target feature value transfer event when the recording service of the target IoT terminal is enabled and the target feature value transfer event is completed for the target object. The target image data stream includes multiple ordered target images.

[0015] The generation unit is used to generate and store a target data stream file based on the target image data stream and the target event identifier corresponding to the target feature value transfer event. The target data stream file is used to trace the target feature value transfer event.

[0016] The sending unit is used to send the target data stream file to the server.

[0017] Optionally, the acquisition unit is used for:

[0018] The color image data stream corresponding to the target feature value transfer event is acquired synchronously and used as the target image data stream.

[0019] Optionally, the acquisition unit is used for:

[0020] The system synchronously acquires a first image data stream of the target feature value transfer event from the start time of the event to the end time of the event, and a second image data stream within a preset time period. The preset time period includes one or more of the first time period before the start time of the event and the second time period after the end time of the event.

[0021] The first image data stream and the second image data stream are determined as the target image data stream.

[0022] Optionally, the device further includes an opening unit, the opening unit being configured to:

[0023] Enable the recording service based on the enabled settings command; or...

[0024] When the actual scenario for feature value transfer is detected to meet abnormal conditions, the recording service is started. The abnormal conditions include the number of objects for feature value transfer being greater than or equal to a preset number or the state of the objects for feature value transfer being abnormal.

[0025] Optionally, the device further includes a prompting unit, the prompting unit being used for:

[0026] The target object is notified that the target feature value transfer event has been recorded and the target data stream file has been generated;

[0027] The target object is prompted that the target data stream file is in a data protection state, which indicates that the target object has authorized access to the target data stream file.

[0028] Optional, the transmitting unit is used for:

[0029] If the target IoT terminal is in an idle state, the target data stream file is sent to the server.

[0030] On the other hand, this application provides a data stream processing apparatus based on eigenvalue transfer, the apparatus comprising: a receiving unit and a storage unit;

[0031] The receiving unit is used to receive a target data stream file sent by the target IoT terminal. The target data stream file is generated based on the target image data stream and the target event identifier corresponding to the target feature value transfer event completed by the target object. The target data stream file is used to trace the target feature value transfer event. The target image data stream includes multiple ordered target images.

[0032] The storage unit is used to store the target data stream file.

[0033] Optionally, the storage unit is used for:

[0034] Extract the target event identifier from the target data stream file as a file index;

[0035] The target data stream file is stored according to the file index.

[0036] Optionally, the apparatus further includes a calling unit, the calling unit being configured to:

[0037] If the target object grants the target data stream file access permission, the target data stream file is invoked based on the target event identifier.

[0038] Optionally, the receiving unit is further configured to:

[0039] Obtain the setting data of the recording service;

[0040] The storage unit is also used for:

[0041] The recording service and the settings data are stored together.

[0042] The device further includes an updating unit, the updating unit being configured to:

[0043] If updated settings data is obtained, the stored settings data is updated synchronously based on the updated settings data.

[0044] On the other hand, this application provides a computer device for data stream processing based on eigenvalue transfer, the computer device including a processor and a memory:

[0045] The memory is used to store program code and transmit the program code to the processor;

[0046] The processor is used to execute the feature-value-based data stream processing method described above, according to the instructions in the program code.

[0047] On the other hand, embodiments of this application provide a computer-readable storage medium for storing a computer program for executing the data stream processing method based on eigenvalue transfer described above.

[0048] On the other hand, embodiments of this application provide a computer program product, which includes a computer program or instructions; when the computer program or instructions are executed by a processor, the data stream processing method based on feature value transfer described above is performed.

[0049] As can be seen from the above technical solution, when the recording service of the target IoT terminal is enabled, for a target object completing a target feature value transfer event on the target IoT terminal, the target IoT terminal needs to synchronously acquire the target image data stream corresponding to the target feature value transfer event. This target image data stream includes multiple ordered target images to record the target feature value transfer event. The target IoT terminal associates the target image data stream with the target event identifier corresponding to the target feature value transfer event to generate and store a target data stream file. This target data stream file can then trace the target feature value transfer event. The target IoT terminal sends the target data stream file to the server so that the server can store the target data stream file. Therefore, in a feature value transfer scenario, enabling the recording service of the target IoT terminal allows the recording of a target object completing a target feature value transfer event on the target IoT terminal, obtaining the target image data stream corresponding to the target feature value transfer event, associating it with the target event identifier corresponding to the target feature value transfer event, generating and storing a target data stream file that can trace the target feature value transfer event, so that it can be subsequently uploaded to the server for storage. Based on this, when payment disputes arise due to misidentification or malicious identification, the target data stream file can be invoked to trace the target feature value transfer event, thereby facilitating the handling of the payment dispute. Attached Figure Description

[0050] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0051] Figure 1 A schematic diagram of an Internet of Things (IoT) terminal provided in an embodiment of this application;

[0052] Figure 2 This is a schematic diagram illustrating an application scenario of a data stream processing method based on eigenvalue transfer, provided in an embodiment of this application.

[0053] Figure 3 A signaling interaction diagram of a data stream processing system based on eigenvalue transfer provided in this application embodiment;

[0054] Figure 4 A schematic diagram of the architecture of a data stream processing system based on feature value transfer is provided for an embodiment of this application;

[0055] Figure 5 A schematic diagram of a data stream processing device based on feature value transfer provided in an embodiment of this application;

[0056] Figure 6 A schematic diagram of another data stream processing apparatus based on feature value transfer provided in an embodiment of this application;

[0057] Figure 7 This is a schematic diagram of the structure of a terminal device provided in an embodiment of this application;

[0058] Figure 8 This is a schematic diagram of the structure of a server provided in an embodiment of this application. Detailed Implementation

[0059] The embodiments of this application will now be described with reference to the accompanying drawings.

[0060] In related technologies, users do not need to carry or use their own mobile phones when shopping; they can directly use the IoT terminal provided by the merchant, such as... Figure 1 The diagram illustrates an IoT terminal that enables electronic payments via facial recognition. However, this facial recognition-based electronic payment method is prone to issues such as misidentification (e.g., when user A performs facial recognition on the IoT terminal, the terminal captures user B's facial image and performs facial recognition on user B), leading to payment disputes; or malicious identification (e.g., user C forcing user D to perform facial recognition on the IoT terminal), also resulting in payment disputes. However, facial recognition-based electronic payment primarily focuses on how to perform facial recognition to achieve electronic payments—that is, how to exchange facial images for user identity information to complete electronic payments—and is insufficient to handle the aforementioned payment disputes.

[0061] In view of this, this application proposes a data stream processing method and related apparatus based on feature value transfer. In a feature value transfer scenario, by enabling the recording service of the target IoT terminal, the target object can complete the recording of the target feature value transfer event on the target IoT terminal, obtaining the target image data stream corresponding to the target feature value transfer event. By associating the target event identifier corresponding to the target feature value transfer event, a target data stream file that can trace the target feature value transfer event can be generated and stored for subsequent uploading to a server for storage. Based on this, in the event of a payment dispute due to misidentification or malicious identification, the target data stream file can be invoked to trace the target feature value transfer event, thereby facilitating the handling of the payment dispute.

[0062] The feature-value transfer-based data stream processing method provided in this application can be applied to feature-value transfer-based data stream processing devices with data processing capabilities, such as servers and terminal devices. The server can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. The terminal device can be a smartphone, computer, personal digital assistant (PDA), tablet computer, laptop computer, desktop computer, intelligent voice interaction device, smart home appliance, in-vehicle terminal, etc., but is not limited to these. The terminal device and the server can be directly or indirectly connected via wired or wireless communication, which is not limited herein.

[0063] Furthermore, the data stream processing method based on feature value transfer provided in this application can be applied to various scenarios, including but not limited to cloud technology, artificial intelligence, and smart transportation.

[0064] The data stream processing method based on eigenvalue transfer provided in this application is implemented based on artificial intelligence (AI). AI is the theory, method, technology, and application system that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to obtain optimal results. In other words, AI is a comprehensive technology within computer science that attempts to understand the essence of intelligence and produce a new type of intelligent machine that can react in a way similar to human intelligence. AI studies the design principles and implementation methods of various intelligent machines, enabling them to possess perception, reasoning, and decision-making capabilities.

[0065] Artificial intelligence (AI) is a comprehensive discipline encompassing a wide range of fields, including both hardware and software technologies. Fundamental AI technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, big data processing, operating / interactive systems, and mechatronics. AI software technologies primarily include computer vision, speech processing, natural language processing, and machine learning / deep learning.

[0066] In the embodiments of this application, the main artificial intelligence technologies involved include computer vision technology. For example, it may involve image processing, image recognition (IR), face recognition, and other biometric identification technologies (BIT) within computer vision (CV).

[0067] This feature-value transfer-based data stream processing device possesses computer vision capabilities. Computer vision (CV) is a science that studies how to enable machines to "see." More specifically, it refers to machine vision, which uses cameras and computers to replace human eyes for target recognition, tracking, and measurement, and further performs image processing to create images more suitable for human observation or transmission to instruments for detection. As a scientific discipline, computer vision researches related theories and technologies, attempting to build artificial intelligence systems capable of extracting information from images or multidimensional data. Computer vision technologies typically include image processing, image recognition, image semantic understanding, image retrieval, OCR, video processing, video semantic understanding, video content / behavior recognition, 3D object reconstruction, 3D technology, virtual reality, augmented reality, simultaneous localization and mapping (SLAM), and common biometric recognition technologies such as facial recognition and fingerprint recognition.

[0068] It is understood that in the specific implementation of the embodiments of this application, the target object can be the target user, etc., which involves user-related data. When the embodiments of this application are applied to specific products or technologies, user permission or consent is required, and the collection, use and processing of related data must comply with the relevant laws, regulations and standards of the relevant countries and regions.

[0069] To facilitate understanding of the technical solution of this application, the data stream processing method based on feature value transfer provided in the embodiments of this application will be introduced below in conjunction with actual application scenarios.

[0070] See Figure 2 , Figure 2 This diagram illustrates an application scenario for a data stream processing method based on eigenvalue transfer, as provided in an embodiment of this application. Figure 2 The application scenario shown includes a target IoT terminal 201 and a server 202. The target IoT terminal 201 is provided by the merchant. The target object completes the target feature value transfer event through facial recognition on the target IoT terminal 201. The target feature value transfer event is the event in which the target object transfers its own feature value to the merchant object.

[0071] Merchants can set the recording service of the target IoT terminal 201 to be enabled, or the target IoT terminal 201 can enable the recording service when it detects that the actual scene meets the preset abnormal conditions. The abnormal conditions can be that the number of objects to be transferred is greater than or equal to a preset number, or that the state of the objects to be transferred meets the abnormal state, and the preset number is greater than or equal to 2.

[0072] If the recording service of the target IoT terminal 201 is enabled, a target feature value transfer event is completed for the target object, and the target image data stream corresponding to the target feature value transfer event is acquired synchronously. The target image data stream includes multiple ordered target images. For example, when the recording service of the target IoT terminal 201 is enabled, a target feature value transfer event E is performed for target object user a who transfers their own feature value to the merchant through facial recognition on the target IoT terminal 201. a Synchronously acquire the target feature value transfer event E a The corresponding target image data stream P a .

[0073] The target IoT terminal 201 generates and stores a target data stream file based on the target image data stream and the target event identifier corresponding to the target feature value transfer event. The target data stream file is used to trace the target feature value transfer event. For example, the target IoT terminal 201 stores the aforementioned target image data stream P a With the aforementioned target eigenvalue transfer event E a Corresponding target event identifier I a Associated to generate target data stream file D a And store the target data stream file D. a The target event identifier I can be used a The name is used to trace the target feature value transfer event E. a .

[0074] The target IoT terminal 201 sends a target data stream file to the server 202; correspondingly, the server 202 receives the target data stream file sent by the target IoT terminal 201. For example, the target IoT terminal 201 sends the aforementioned target data stream file D to the server 202. a If the transmission is successful, server 202 will receive the target data stream file D. a .

[0075] Server 202 stores the target data stream file. For example, server 202 can store the received target data stream file D. a Store it so that the target data stream file D can be accessed later. a Used to trace the aforementioned target feature value transfer event E a .

[0076] As can be seen, in the feature value transfer scenario, when the target IoT terminal 201 activates its recording service, the target object can record the target feature value transfer event on the target IoT terminal, obtaining the target image data stream corresponding to the target feature value transfer event. By associating the target event identifier with the target event identifier, a target data stream file that can trace the target feature value transfer event can be generated and stored for subsequent uploading to server 202. Based on this, in the event of a payment dispute due to misidentification or malicious identification, the target data stream file can be called to trace the target feature value transfer event, thereby facilitating the handling of the payment dispute.

[0077] The following section uses the target IoT terminal and server as data stream processing devices based on feature value transfer to describe in detail the interaction process between the feature value transfer-based data stream processing method provided in this application embodiment and the target IoT terminal and server.

[0078] See Figure 3 This figure is a signaling interaction diagram of a data stream processing system based on eigenvalue transfer provided in an embodiment of this application. Figure 3 As shown, the eigenvalue-based data stream processing system includes a target IoT terminal and a server, which serve as eigenvalue-based data stream processing devices.

[0079] S301: If the recording service of the target IoT terminal is enabled, the target IoT terminal completes the target feature value transfer event for the target object and synchronously acquires the target image data stream corresponding to the target feature value transfer event. The target image data stream includes multiple ordered target images.

[0080] Because users don't need to carry or use their own mobile phones when shopping, they can complete electronic payments directly through facial recognition on the IoT terminals provided by merchants. However, the aforementioned facial recognition-based electronic payment method can lead to payment disputes in cases of misidentification or malicious identification. Since this method primarily focuses on how to perform facial recognition for electronic payments, it is insufficient to handle such payment disputes.

[0081] Therefore, this application can simultaneously record the entire electronic payment process using an IoT terminal while the user completes the electronic payment via facial recognition. This record provides a data foundation for subsequent traceability of the entire electronic payment process. In this embodiment, any purchasing user is considered the target object, and any IoT terminal provided by any merchant is considered the target IoT terminal. The entire process of the target object completing the electronic payment via facial recognition on the target IoT terminal is the event of the target object transferring its own feature value to the merchant object, which is considered a target feature value transfer event. It is necessary to simultaneously record this target feature value transfer event using the target IoT terminal to record the event and provide a data foundation for subsequent traceability of the target feature value transfer event.

[0082] The prerequisite for recording the target feature value transfer event is that the recording service of the target IoT terminal is enabled. On this basis, the target feature value transfer event is completed for the target object, and the target feature value transfer event is recorded synchronously, which means synchronously acquiring the target image data stream corresponding to the target feature value transfer event; wherein, the target image data stream includes multiple ordered target images.

[0083] The activation of the recording service on the target IoT terminal can be divided into two methods: The first method involves the merchant setting the recording service on the target IoT terminal themselves. In this case, the target IoT terminal responds to the merchant's setting operation by generating an activation command for the recording service, and then activates the recording service according to the command. The second method involves the target IoT terminal automatically detecting the actual scenario where feature values ​​need to be transferred. If the number of objects to be transferred is greater than or equal to a pre-set number, or if the state of the objects to be transferred meets a pre-set abnormal state, it indicates that the actual scenario meets abnormal conditions and the recording service needs to be automatically activated. Therefore, this application provides a possible implementation method. Before S301, the method may also include, for example, the following S1 or S2:

[0084] S1: The target IoT terminal starts the recording service based on the recording service start setting command.

[0085] As an example, the target IoT terminal provides a setting control for the recording service, which can set the recording service to be enabled or disabled. The recording service is disabled by default. Merchants can view the current actual scene and, based on the actual scene's pedestrian flow or abnormal situation, enable the recording service themselves through this setting control. Then, the target IoT terminal can receive the instruction to enable the recording service and enable the recording service through this instruction.

[0086] S2: When the target IoT terminal detects that the actual scene to be transferred meets the abnormal conditions, the recording service is started. The abnormal conditions include the number of objects to be transferred being greater than or equal to a preset number or the state of the objects to be transferred being abnormal, and the preset number being greater than or equal to 2.

[0087] As an example, the target IoT terminal can automatically detect the actual scene to be transferred using its 3D camera. When the number of objects to be transferred is greater than or equal to a preset number of 2, it indicates that the actual scene meets the abnormal conditions; that is, there may be misidentification of 2 or 3 objects to be transferred in the actual scene, and the recording service needs to be started automatically.

[0088] As another example, the target IoT terminal can automatically detect the actual scene to be transferred using its 3D camera. If the detected object to be transferred is in an abnormal state, such as an abnormal facial expression or abnormal behavior, it means that the detected actual scene meets the abnormal conditions. That is, the object to be transferred in the actual scene that meets the abnormal facial expression or abnormal behavior may be subject to malicious identification, and the recording service needs to be automatically started.

[0089] The target object completing the target feature value transfer event refers to the target object performing face recognition on the target IoT terminal. The face recognition application (APP) installed on the target IoT terminal can generate a unique identifier corresponding to the target feature value transfer event based on the terminal identifier of the target IoT terminal, the merchant identifier of the target IoT terminal, and the transfer time of the target feature value transfer event using a preset algorithm. This identifier serves as the target event identifier corresponding to the target feature value transfer event. The target IoT terminal collects the relevant image data streams corresponding to the target feature value transfer event through its 3D camera, namely, color image data stream, depth image data stream, and infrared image data stream.

[0090] Based on the above description, synchronously acquiring the target image data stream corresponding to the target feature value transfer event can involve synchronously acquiring the color image data stream, depth image data stream, and infrared image data stream corresponding to the target feature value transfer event. However, considering the limited storage space of the target IoT terminal, and to reduce the burden on the target IoT terminal, synchronously acquiring the target image data stream corresponding to the target feature value transfer event can be limited to synchronously acquiring only the color image data stream corresponding to the target feature value transfer event. Therefore, this application provides a possible implementation method where the step of synchronously acquiring the target image data stream corresponding to the target feature value transfer event in S301 can, for example, include: the target IoT terminal synchronously acquiring the color image data stream corresponding to the target feature value transfer event as the target image data stream.

[0091] Furthermore, in addition to synchronously recording the entire electronic payment process using an IoT terminal, this application also considers that the scene information before and after the electronic payment process may have a certain causal relationship with the entire electronic payment process. Therefore, it is also necessary to synchronously record the scene information before and after the electronic payment process using an IoT terminal to record the scene information before and after the electronic payment process, so as to provide a richer and more sufficient data foundation for tracing the entire electronic payment process in the future.

[0092] Based on this, in addition to synchronously recording the target feature value transfer event using the target IoT terminal (i.e., synchronously acquiring the first image data stream of the target feature value transfer event from the event start time to the event end time), it is also necessary to synchronously record one or more of the scene information before and after the target feature value transfer event using the IoT terminal. This means synchronously acquiring one or more of the image data streams of the first time period before the event start time and the second time period after the event end time, which serve as the second image data stream of the target feature value transfer event within a preset time period. Based on this, the first image data stream combined with the second image data stream constitutes the target image data stream corresponding to the target feature value transfer event. Therefore, this application provides a possible implementation method. The step of synchronously acquiring the target image data stream corresponding to the target feature value transfer event in S301 may include, for example, the following S3011-S3012:

[0093] S3011: The target IoT terminal synchronously acquires the first image data stream of the target feature value transfer event from the start time of the event to the end time of the event, and the second image data stream during a preset time period. The preset time period includes one or more of the first time period before the start time of the event and the second time period after the end time of the event.

[0094] S3012: The target IoT terminal determines the first image data stream and the second image data stream as the target image data stream.

[0095] As an example, target user A completes target feature value transfer event E at the target IoT terminal. a The event starts at 18:00 and ends at 18:05; therefore, the target feature value transfer event E is completed for target user A. a The target IoT terminal synchronously acquires the target feature value transfer event E. a The target IoT terminal identifies the aforementioned first and second image data streams as the target feature value transfer event E, which includes a portion of the second image data stream during the first time period from 17:58 to 18:00 before the event start time of 18:00, the first image data stream from the event start time of 18:00 to the event end time of 18:00, and another portion of the second image data stream during the second time period from 18:00 to 18:02 after the event end time of 18:00. a The corresponding target image data stream P a .

[0096] S302: The target IoT terminal generates and stores a target data stream file based on the target image data stream and the target event identifier corresponding to the target feature value transfer event. The target data stream file is used to trace the target feature value transfer event.

[0097] In this embodiment, after the target IoT terminal synchronously acquires the target image data stream corresponding to the target feature value transfer event in S301, it is also necessary to associate the target image data stream with the target event identifier corresponding to the aforementioned target feature value transfer event to generate a target data stream file for tracing the target feature value transfer event. The target data stream file is then associated with the target feature value transfer event through the target event identifier and stored locally on the target IoT terminal, which is equivalent to caching the target data stream file locally on the target IoT terminal. This target data stream file can be a target tracing video file.

[0098] In this process, associating the target image data stream with the target event identifier corresponding to the target feature value transfer event to generate the target data stream file can be achieved by naming the target data stream file using the target event identifier corresponding to the target feature value transfer event. Therefore, this application provides a possible implementation method in which the target data stream file is named with the target event identifier.

[0099] Furthermore, in this embodiment, after the target data stream file is generated by S302, the target data stream file is equivalent to a file generated by recording the target object completing the target feature value transfer event on the target IoT terminal. If the target object is the object being recorded, it is also necessary to notify the target object that the target feature value transfer event has been recorded and a target data stream file has been generated. Based on this, it is also necessary to notify the target object that the target data stream file is in a data protection state where the calling permission is authorized by the target object. Therefore, this application provides a possible implementation method, which may further include, for example, the following S3-S4:

[0100] S3: The target IoT terminal notifies the target object that the target feature value transfer event has been recorded and a target data stream file has been generated.

[0101] As an example, when the target IoT terminal displays the result page of the target feature value transfer event, in addition to showing the result of the target feature value transfer event to the target object, the result page also simultaneously prompts the target object that the target feature value transfer event has been recorded and generated into a target data stream file.

[0102] S4: The target IoT terminal prompts the target object that the target data stream file is in a data protection state. The data protection state means that the target object has authorized access to the target data stream file.

[0103] As an example, based on the above example, the target IoT terminal can also simultaneously notify the target object that the target data stream file is in a data protection state; that is, it notifies the target object that the target data stream file can only be accessed if the target object authorizes the access permission to access the target data stream file.

[0104] S303: The target IoT terminal sends the target data stream file to the server.

[0105] In this embodiment of the application, after the target IoT terminal generates the target data stream file in S302, and the target IoT terminal stores the target data stream file, it is also necessary to send the target data stream file to the server so that the server can obtain the target data stream file that can trace the target feature value transfer event.

[0106] In this application, considering that when the target IoT terminal is in an active state, processor resources are mainly used to complete the target feature value transfer event and the aforementioned S301-S302, in order to avoid occupying processor resources when the target IoT terminal is in an active state, the target data stream file can be sent to the server only when the target IoT terminal is in an idle state, provided that the target IoT terminal has already stored the target data stream file. Therefore, this application provides a possible implementation method, and S303 may include, for example, sending the target data stream file to the server if the target IoT terminal is in an idle state. For example, the target IoT terminal silently uploads the target data stream file to the server.

[0107] Furthermore, in this embodiment, based on the above description, considering the limited storage space of the target IoT terminal, in order to alleviate the burden on the target IoT terminal, after the target IoT terminal successfully sends the target data stream file to the server, it is also necessary to delete the target data stream file stored in S302 to provide more storage space. Therefore, this application provides a possible implementation, and the method may further include, for example, S5: if the target data stream file is successfully sent to the server, the target IoT terminal deletes the stored target data stream file.

[0108] If the target data stream file is successfully sent to the server, the target IoT terminal can either delete the stored target data stream file immediately or delete it periodically. The specific implementation method can be set according to the specific scenario.

[0109] S304: The server receives the target data stream file sent by the target IoT terminal.

[0110] In this embodiment of the application, corresponding to the target IoT terminal sending the target data stream file to the server in S303, the server can receive the target data stream file sent by the target IoT terminal.

[0111] S305: Server stores target data stream files.

[0112] In this embodiment, after the S304 server receives the target data stream file, in addition to using the target data stream file to trace target feature value transfer events, the server also needs to store the target data stream file in a local file library. This file library is a lightweight database, such as a relational database management system, so that the target feature value transfer events can be traced based on it in the future, thereby improving the efficiency and accuracy of tracing target feature value transfer events.

[0113] To facilitate faster and more convenient retrieval of the target data stream file for tracing target feature value transfer events, when storing the target data stream file, the target event identifier corresponding to the target feature value transfer event in the target data stream file can be extracted first as a file index. Then, the target data stream file is stored corresponding to this file index. This allows direct retrieval of the target data stream file via the file index of the target event identifier, thus facilitating faster and more convenient tracing of target feature value transfer events. Therefore, this application provides a possible implementation method, and S305 may include, for example, the following S3051-S3052:

[0114] S3051: The server extracts the target event identifier from the target data stream file as a file index;

[0115] S3052: The server corresponds to the file index storage of the target data stream file.

[0116] Furthermore, in the implementation of this application, when it is necessary to call the target data stream file to trace target feature value transfer events, and to facilitate handling payment disputes arising from misidentification or malicious identification of the target feature value transfer event, it is necessary to obtain authorization from the target object to call the target data stream file, and to call the target data stream file according to the target event identifier. Therefore, this application provides a possible implementation method, which may further include, for example, S6: if the target object authorizes the calling permission of the target data stream file, the server calls the target data stream file according to the target event identifier.

[0117] Furthermore, in this implementation, the server can also record the setting data of the recording service of the target IoT terminal so that the setting data of the recording service of the target IoT terminal can be viewed later; the server can obtain the setting data of the recording service of the target IoT terminal and associate and store the recording service and setting data. When updated setting data is obtained, the stored setting data is updated synchronously. Therefore, this application provides a possible implementation method, which may also include S7-S9:

[0118] S7: The server retrieves the recording service settings data;

[0119] S8: The server will store the recording service and settings data together;

[0120] S9: If updated settings data is obtained, the server will synchronously update the stored settings data based on the updated data.

[0121] The data stream processing method based on feature value transfer provided in the above embodiments, when the recording service of the target IoT terminal is enabled, requires the target IoT terminal to synchronously acquire the target image data stream corresponding to the target feature value transfer event when the target object completes the target feature value transfer event on the target IoT terminal. This target image data stream includes multiple ordered target images to record the target feature value transfer event. The target IoT terminal associates the target image data stream with the target event identifier corresponding to the target feature value transfer event to generate and store a target data stream file. This target data stream file can then trace the target feature value transfer event. The target IoT terminal sends the target data stream file to the server so that the server can store the target data stream file. Therefore, in a feature value transfer scenario, enabling the recording service of the target IoT terminal allows the recording of the target object completing the target feature value transfer event on the target IoT terminal, obtaining the target image data stream corresponding to the target feature value transfer event, associating it with the target event identifier corresponding to the target feature value transfer event, generating and storing a target data stream file that can trace the target feature value transfer event, so that it can be subsequently uploaded to the server for storage. Based on this, when payment disputes arise due to misidentification or malicious identification, the target data stream file can be invoked to trace the target feature value transfer event, thereby facilitating the handling of the payment dispute.

[0122] See Figure 4 This figure is a schematic diagram of the architecture of a feature-value transfer-based data stream processing system provided in an embodiment of this application. The feature-value transfer-based data stream processing system includes two parts: an IoT face terminal device 410 and a server 420. These two parts will be described in detail below.

[0123] Part 1: Internet of Things (IoT) facial recognition terminal device 410.

[0124] The IoT face terminal device 410 runs a face recognition APP, which includes a camera management module 411, a face recognition module 412, a recording module 413, a settings module 414, and a results module 415.

[0125] The setting module 414 is used by the merchant to view the current actual scene and set whether the recording service provided by the IoT face terminal device 410 is enabled based on the actual scene’s traffic or abnormal situation. It is disabled by default. The recording module 413 will enable the recording service after the merchant sets it to be enabled, and will record the target feature value transfer event synchronously.

[0126] The camera management module 411 is used for target feature value transfer events during face recognition of the target object on the IoT face terminal device 410. The face recognition app calculates and generates a unique identifier corresponding to the target feature value transfer event based on the terminal identifier of the IoT face terminal device 410, the merchant identifier where the IoT face terminal device 410 is located, and the transfer time of the target feature value transfer event, using certain rules. This unique identifier serves as the target event identifier for the target feature value transfer event. The module also acquires the relevant image data streams corresponding to the target feature value transfer event collected by the 3D camera, namely, color image data stream, depth image data stream, and infrared image data stream.

[0127] Recording module 413 includes data recording module 4131 and file generation module 4132:

[0128] The data recording module 4131 is used to, when the recording service provided by the IoT face terminal device 410 is enabled, synchronously acquire the target image data stream corresponding to the target feature value transfer event when the target object completes the target feature value transfer event on the IoT face terminal device 410. The target image data stream includes multiple ordered target images to record the target feature value transfer event. Considering that the storage space of the IoT face terminal device 410 is limited, only the color image data stream corresponding to the target feature value transfer event is synchronously acquired as the target image data stream.

[0129] The file generation module 4132 is used to associate the target image data stream with the target event identifier corresponding to the target feature value transfer event to generate and store a target data stream file. This target data stream file is named with the target event identifier and can trace the target feature value transfer event. The target data stream file is silently uploaded to the server 420. If the target data stream file is successfully sent to the server 420, the stored target data stream file is deleted.

[0130] The face recognition module 412 includes a face acquisition module 4121 and a face selection module 4122:

[0131] Among them, the face acquisition module 4121 is used to acquire the face image data stream of the target object captured by the 3D camera through the face APP.

[0132] The face selection module 4122 is used to select the best face image from the face image data stream. The selection process uses a comprehensive evaluation of factors such as face size, face angle, image contrast, image brightness, and sharpness to choose the optimal face image. This optimal face image is then uploaded to the server 420.

[0133] When the IoT face terminal device 410 displays the result page of the target feature value transfer event, the result module 415, in addition to showing the result of the target feature value transfer event to the target object, simultaneously prompts the target object that the target feature value transfer event has been recorded and generated into a target data stream file. It can also simultaneously prompt the target object that the target data stream file is in a data protection state; that is, it prompts the target object that the target data stream file can only be accessed if the target object authorizes the access permission to access the target data stream file.

[0134] Part Two: Server 420.

[0135] The core of server 420 includes face recognition service 421, basic account service 422, basic payment service 423, face recognition payment traceability service 424, and face recognition payment recording management service 425.

[0136] The face recognition service 421 is used to receive the best face image uploaded by the face optimization module 4122 in the IoT face terminal device 410, extract face features from the best face image, compare the face features with the face features in the face feature database, find the face feature with the highest score, and compare the face feature with the face in the face database. After successful comparison, the relevant information of the target object's account or payment code is sent to the IoT face terminal device 410.

[0137] Basic account service 422, namely, account system relationship chain related services, is used to obtain the identity information of the target object after successful facial recognition.

[0138] Basic payment service 423 is a backend service used for payments based on information related to the payment code obtained from the optimal facial image.

[0139] The facial recognition payment tracing service 424 is used to receive and store the target data stream file uploaded by the file generation module 4132 in the IoT facial recognition terminal device 410. When storing the target data stream file, the target event identifier corresponding to the target feature value transfer event in the target data stream file can be extracted first as a file index. Then, the target data stream file is stored corresponding to this file index. This allows the target data stream file to be directly accessed by using the target event identifier in this file index, making it more convenient and faster to trace the target feature value transfer event.

[0140] The face recognition payment recording management service 425 is used to obtain the recording service settings data provided by the IoT face terminal device 410 in the setting module 414, and associate and store the recording service and the setting data. When the updated setting data is obtained, the stored setting data is updated synchronously.

[0141] In feature value transfer scenarios, enabling the recording service of IoT face recognition terminal devices allows for the recording of target feature value transfer events on the target object. This results in a target image data stream corresponding to the feature value transfer event. By associating this stream with a target event identifier, a traceable target data stream file can be generated and stored for later uploading to a server. Based on this, in cases of payment disputes arising from misidentification or malicious identification, the target data stream file can be invoked to trace the target feature value transfer event, thus facilitating the resolution of such disputes.

[0142] In view of the data stream processing method based on feature value transfer provided in the above embodiments, this application also provides a data stream processing apparatus based on feature value transfer.

[0143] See Figure 5 , Figure 5 This is a schematic diagram of a data stream processing device based on feature value transfer, provided as an embodiment of this application. Figure 5 As shown, the data stream processing device 500 based on feature value transfer includes an acquisition unit 501, a generation unit 502, and a transmission unit 503;

[0144] The acquisition unit 501 is used to acquire the target image data stream corresponding to the target feature value transfer event when the recording service of the target IoT terminal is enabled, and the target feature value transfer event is completed for the target object. The target image data stream includes multiple ordered target images.

[0145] The generation unit 502 is used to generate and store a target data stream file based on the target image data stream and the target event identifier corresponding to the target feature value transfer event. The target data stream file is used to trace the target feature value transfer event.

[0146] The sending unit 503 is used to send the target data stream file to the server.

[0147] As one possible implementation, the acquisition unit 501 is used for:

[0148] The color image data stream corresponding to the target feature value transfer event is acquired synchronously and used as the target image data stream.

[0149] As one possible implementation, the acquisition unit 501 is used for:

[0150] The system synchronously acquires a first image data stream of the target feature value transfer event from the start time of the event to the end time of the event, and a second image data stream within a preset time period. The preset time period includes one or more of the first time period before the start time of the event and the second time period after the end time of the event.

[0151] The first image data stream and the second image data stream are determined as the target image data stream.

[0152] As one possible implementation, the device further includes an opening unit, the opening unit being configured to:

[0153] Enable the recording service based on the enabled settings command; or...

[0154] When the actual scenario for feature value transfer is detected to meet abnormal conditions, the recording service is started. The abnormal conditions include the number of objects for feature value transfer being greater than or equal to a preset number or the state of the objects for feature value transfer being abnormal.

[0155] As one possible implementation, the device further includes a prompting unit, the prompting unit being configured to:

[0156] The target object is notified that the target feature value transfer event has been recorded and the target data stream file has been generated;

[0157] The target object is prompted that the target data stream file is in a data protection state, which indicates that the target object has authorized access to the target data stream file.

[0158] As one possible implementation, the sending unit 503 is used for:

[0159] If the target IoT terminal is in an idle state, the target data stream file is sent to the server.

[0160] The feature-value transfer-based data stream processing device provided in the above embodiments, when the recording service of the target IoT terminal is enabled, requires the target IoT terminal to synchronously acquire the target image data stream corresponding to the target feature value transfer event when the target object completes the target feature value transfer event on the target IoT terminal. This target image data stream includes multiple ordered target images to record the target feature value transfer event. The target IoT terminal associates the target image data stream with the target event identifier corresponding to the target feature value transfer event to generate and store a target data stream file. This target data stream file can then trace the target feature value transfer event. The target IoT terminal sends the target data stream file to the server for storage. Therefore, in a feature value transfer scenario, enabling the recording service of the target IoT terminal allows the recording of the target object completing the target feature value transfer event on the target IoT terminal, obtaining the target image data stream corresponding to the target feature value transfer event, associating it with the target event identifier, and generating and storing a target data stream file that can trace the target feature value transfer event for subsequent uploading to the server for storage. Based on this, when payment disputes arise due to misidentification or malicious identification, the target data stream file can be invoked to trace the target feature value transfer event, thereby facilitating the handling of the payment dispute.

[0161] This application also provides another data stream processing apparatus based on eigenvalue transfer. See also Figure 6 , Figure 6 This is a schematic diagram of another data stream processing apparatus based on feature value transfer, provided as an embodiment of this application. Figure 6 As shown, the data stream processing device 600 based on feature value transfer includes a receiving unit 601 and a storage unit 602;

[0162] The receiving unit 601 is used to receive a target data stream file sent by the target IoT terminal. The target data stream file is generated based on the target image data stream and the target event identifier corresponding to the target feature value transfer event completed by the target object. The target data stream file is used to trace the target feature value transfer event. The target image data stream includes multiple ordered target images.

[0163] The storage unit 602 is used to store the target data stream file.

[0164] As one possible implementation, the storage unit 602 is used for:

[0165] Extract the target event identifier from the target data stream file as a file index;

[0166] The target data stream file is stored according to the file index.

[0167] As one possible implementation, the apparatus further includes a calling unit, the calling unit being configured to:

[0168] If the target object grants the target data stream file access permission, the target data stream file is invoked based on the target event identifier.

[0169] As one possible implementation, the receiving unit 601 is further configured to:

[0170] Obtain the setting data of the recording service;

[0171] The storage unit 602 is also used for:

[0172] The recording service and the settings data are stored together.

[0173] The device further includes an updating unit, the updating unit being configured to:

[0174] If updated settings data is obtained, the stored settings data is updated synchronously based on the updated settings data.

[0175] The feature-value transfer-based data stream processing device provided in the above embodiments, when the recording service of the target IoT terminal is enabled, requires the target IoT terminal to synchronously acquire the target image data stream corresponding to the target feature value transfer event when the target object completes the target feature value transfer event on the target IoT terminal. This target image data stream includes multiple ordered target images to record the target feature value transfer event. The target IoT terminal associates the target image data stream with the target event identifier corresponding to the target feature value transfer event to generate and store a target data stream file. This target data stream file can then trace the target feature value transfer event. The target IoT terminal sends the target data stream file to the server for storage. Therefore, in a feature value transfer scenario, enabling the recording service of the target IoT terminal allows the recording of the target object completing the target feature value transfer event on the target IoT terminal, obtaining the target image data stream corresponding to the target feature value transfer event, associating it with the target event identifier, and generating and storing a target data stream file that can trace the target feature value transfer event for subsequent uploading to the server for storage. Based on this, when payment disputes arise due to misidentification or malicious identification, the target data stream file can be invoked to trace the target feature value transfer event, thereby facilitating the handling of the payment dispute.

[0176] This application also provides a data stream processing device based on feature value transfer. The computer device provided in this application will be described below from the perspective of hardware implementation.

[0177] See Figure 7 , Figure 7 This is a schematic diagram of a terminal device provided in an embodiment of this application. For ease of explanation, only the parts related to the embodiment of this application are shown; for specific technical details not disclosed, please refer to the method section of the embodiment of this application. The terminal device can be any terminal device including mobile phones, tablets, PDAs, etc. Taking a mobile phone as an example:

[0178] Figure 7 This diagram illustrates a partial structural representation of a mobile phone related to the terminal device provided in this embodiment. (Reference) Figure 7 The mobile phone includes components such as a radio frequency (RF) circuit 710, a memory 720, an input unit 730, a display unit 740, a sensor 750, an audio circuit 760, a wireless Fidelity (WiFi) module 770, a processor 780, and a power supply 790. Those skilled in the art will understand that... Figure 7 The mobile phone structure shown does not constitute a limitation on the mobile phone and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0179] The following is combined with Figure 7 A detailed introduction to each component of a mobile phone:

[0180] RF circuit 710 can be used for receiving and transmitting signals during information transmission or calls. Specifically, it receives downlink information from the base station and processes it with processor 780; additionally, it transmits uplink data to the base station. Typically, RF circuit 710 includes, but is not limited to, an antenna, at least one amplifier, a transceiver, a coupler, a low-noise amplifier (LNA), and a duplexer. Furthermore, RF circuit 710 can also communicate wirelessly with networks and other devices. The aforementioned wireless communication can use any communication standard or protocol, including but not limited to Global System for Mobile Communications (GSM), General Packet Radio Service (GPRS), Code Division Multiple Access (CDMA), Wideband Code Division Multiple Access (WCDMA), Long Term Evolution (LTE), email, and Short Messaging Service (SMS).

[0181] The memory 720 can be used to store software programs and modules. The processor 780 runs the software programs and modules stored in the memory 720 to realize various functions and data processing of the mobile phone. The memory 720 may mainly include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created according to the use of the mobile phone (such as audio data, phonebook, etc.). In addition, the memory 720 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0182] The input unit 730 can be used to receive input numerical or character information, and to generate key signal inputs related to user settings and function control of the mobile phone. Specifically, the input unit 730 may include a touch panel 731 and other input devices 732. The touch panel 731, also known as a touch screen, can collect touch operations performed by the user on or near it (such as operations performed by the user using a finger, stylus, or any suitable object or accessory on or near the touch panel 731), and drive the corresponding connected devices according to a pre-set program. Optionally, the touch panel 731 may include two parts: a touch detection device and a touch controller. The touch detection device detects the user's touch position and the signal generated by the touch operation, and transmits the signal to the touch controller; the touch controller receives touch information from the touch detection device, converts it into touch point coordinates, and sends it to the processor 780, and can also receive and execute commands sent by the processor 780. In addition, the touch panel 731 can be implemented using various types such as resistive, capacitive, infrared, and surface acoustic wave. In addition to the touch panel 731, the input unit 730 may also include other input devices 732. Specifically, other input devices 732 may include, but are not limited to, one or more of the following: physical keyboard, function keys (such as volume control buttons, power buttons, etc.), trackball, mouse, joystick, etc.

[0183] The display unit 740 can be used to display information input by the user or information provided to the user, as well as various menus of the mobile phone. The display unit 740 may include a display panel 741, which may optionally be configured as a Liquid Crystal Display (LCD), Organic Light-Emitting Diode (OLED), or similar display panel. Further, a touch panel 731 may cover the display panel 741. When the touch panel 731 detects a touch operation on or near it, it transmits the information to the processor 780 to determine the type of touch event. Subsequently, the processor 780 provides corresponding visual output on the display panel 741 based on the type of touch event. Although in Figure 7 In this embodiment, the touch panel 731 and the display panel 741 are two separate components to realize the input and output functions of the mobile phone. However, in some embodiments, the touch panel 731 and the display panel 741 can be integrated to realize the input and output functions of the mobile phone.

[0184] The mobile phone may also include at least one sensor 750, such as a light sensor, a motion sensor, and other sensors. Specifically, the light sensor may include an ambient light sensor and a proximity sensor. The ambient light sensor can adjust the brightness of the display panel 741 according to the ambient light level, and the proximity sensor can turn off the display panel 741 and / or backlight when the phone is moved to the ear. As a type of motion sensor, an accelerometer sensor can detect the magnitude of acceleration in various directions (generally three axes). When stationary, it can detect the magnitude and direction of gravity and can be used for applications that recognize the phone's posture (such as landscape / portrait switching, related games, magnetometer posture calibration), vibration recognition functions (such as pedometer, taps), etc. Other sensors that may be configured in the mobile phone, such as gyroscopes, barometers, hygrometers, thermometers, and infrared sensors, will not be described in detail here.

[0185] Audio circuit 760, speaker 761, and microphone 762 provide an audio interface between the user and the mobile phone. Audio circuit 760 converts received audio data into electrical signals and transmits them to speaker 761, where speaker 761 converts them into sound signals for output. On the other hand, microphone 762 converts collected sound signals into electrical signals, which are received by audio circuit 760, converted into audio data, and then processed by processor 780 before being transmitted via RF circuit 710 to, for example, another mobile phone, or the audio data can be output to memory 720 for further processing.

[0186] WiFi is a short-range wireless transmission technology. Through the WiFi module 770, mobile phones can help users send and receive emails, browse web pages, and access streaming media, providing users with wireless broadband internet access. Although Figure 7The WiFi module 770 is shown, but it is understood that it is not an essential component of a mobile phone and can be omitted as needed without changing the essence of the invention.

[0187] The processor 780 is the control center of the mobile phone, connecting various parts of the phone through various interfaces and lines. It performs various functions and processes data by running or executing software programs and / or modules stored in the memory 720, and by calling data stored in the memory 720. Optionally, the processor 780 may include one or more processing units; preferably, the processor 780 may integrate an application processor and a modem processor, wherein the application processor mainly handles the operating system, user interface, and applications, and the modem processor mainly handles wireless communication. It is understood that the modem processor may also not be integrated into the processor 780.

[0188] The mobile phone also includes a power supply 790 (such as a battery) that supplies power to various components. Preferably, the power supply can be logically connected to the processor 780 through a power management system, thereby enabling functions such as charging, discharging, and power consumption management through the power management system.

[0189] Although not shown, mobile phones may also include a camera, Bluetooth module, etc., which will not be described in detail here.

[0190] In this embodiment of the application, the memory 720 included in the mobile phone can store program code and transmit the program code to the processor.

[0191] The processor 780 included in the mobile phone can execute the following steps according to the instructions in the program code:

[0192] If the recording service of the target IoT terminal is enabled, the target feature value transfer event is completed for the target object, and the target image data stream corresponding to the target feature value transfer event is acquired synchronously. The target image data stream includes multiple ordered target images.

[0193] Based on the target image data stream and the target event identifier corresponding to the target feature value transfer event, a target data stream file is generated and stored. The target data stream file is used to trace the target feature value transfer event.

[0194] Send the target data stream file to the server.

[0195] In view of the data stream processing method based on eigenvalue transfer described above, this application embodiment also provides a terminal device for data stream processing based on eigenvalue transfer, so that the above-mentioned data stream processing method based on eigenvalue transfer can be implemented and applied in practice.

[0196] See Figure 8 , Figure 8 This is a schematic diagram of a server structure provided in an embodiment of this application. The server 800 can vary significantly due to different configurations or performance. It may include one or more central processing units (CPUs) 822 (e.g., one or more processors) and memory 832, and one or more storage media 830 (e.g., one or more mass storage devices) for storing application programs 842 or data 844. The memory 832 and storage media 830 can be temporary or persistent storage. The program stored in the storage media 830 may include one or more modules (not shown in the diagram), each module may include a series of instruction operations on the server. Furthermore, the CPU 822 may be configured to communicate with the storage media 830 and execute the series of instruction operations in the storage media 830 on the server 800.

[0197] Server 800 may also include one or more power supplies 826, one or more wired or wireless network interfaces 850, one or more input / output interfaces 858, and / or one or more operating systems 841, such as Windows Server. TM Mac OS X TM Unix TM Linux TM FreeBSD TM etc.

[0198] The steps performed by the server in the above embodiments can be based on this Figure 8 The server structure shown.

[0199] The CPU 822 is used to perform the following steps:

[0200] The system receives a target data stream file sent by the target IoT terminal. The target data stream file is generated based on the target image data stream and target event identifier corresponding to the target feature value transfer event completed by the target object. The target data stream file is used to trace the target feature value transfer event. The target image data stream includes multiple ordered target images.

[0201] Store the target data stream file.

[0202] This application also provides a computer-readable storage medium for storing a computer program for executing the feature-value-based data stream processing method provided in the above embodiments.

[0203] This application also provides a computer program product or computer program that includes computer instructions stored in a computer-readable storage medium. A processor for a data stream processing apparatus based on eigenvalue transfer reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the data stream processing apparatus for eigenvalue transfer to perform the data stream processing method based on eigenvalue transfer provided in various optional implementations of the above aspects.

[0204] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium can be at least one of the following media: read-only memory (ROM), RAM, magnetic disk or optical disk, and other media that can store program code.

[0205] It should be noted that the various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, for the device and system embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the description of the method embodiments. The device and system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of the solution in this embodiment according to actual needs. Those skilled in the art can understand and implement this without creative effort.

[0206] The above is merely one specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A data stream processing method based on eigenvalue transfer, characterized in that, The method includes: Enable the recording service based on the recording service enable settings command; or... When the actual scenario of the feature value to be transferred is detected to meet the abnormal conditions, the recording service is automatically started. The abnormal conditions include the number of objects to be transferred being greater than or equal to a preset number or the state of the objects to be transferred being abnormal. The preset number is greater than or equal to 2. For a target object to complete a target feature value transfer event, simultaneously acquire a first image data stream of the target feature value transfer event from the event start time to the event end time and a second image data stream of the target feature value transfer event within a preset time period. The preset time period includes one or more of the first time period before the event start time and the second time period after the event end time. The first image data stream and the second image data stream are determined as the target image data stream corresponding to the target feature value transfer event, and the target image data stream includes multiple ordered target images; Based on the target image data stream and the target event identifier corresponding to the target feature value transfer event, a target data stream file is generated and stored, and the target data stream file is used to trace the target feature value transfer event; The target data stream file is sent to the server.

2. The method according to claim 1, characterized in that, The synchronous acquisition of the target image data stream corresponding to the target feature value transfer event includes: The color image data stream corresponding to the target feature value transfer event is acquired synchronously and used as the target image data stream.

3. The method according to any one of claims 1-2, characterized in that, The method further includes: The target object is notified that the target feature value transfer event has been recorded and the target data stream file has been generated; The target object is prompted that the target data stream file is in a data protection state, which indicates that the target object has authorized access to the target data stream file.

4. The method according to any one of claims 1-2, characterized in that, Sending the target data stream file to the server includes: If the target IoT terminal is in an idle state, the target data stream file is sent to the server.

5. A data stream processing method based on eigenvalue transfer, characterized in that, The method includes: The system receives a target data stream file sent by a target IoT terminal. The target data stream file is generated based on the target image data stream and target event identifier corresponding to the target feature value transfer event completed by the target object. The target data stream file is used to trace the target feature value transfer event. The target image data stream includes multiple ordered target images. Store the target data stream file; The process of generating the target image data stream includes: when the target IoT terminal starts recording service, completing the target feature value transfer event for the target object, and synchronously acquiring the first image data stream of the target feature value transfer event from the event start time to the event end time and the second image data stream in a preset time period, wherein the preset time period includes one or more of the first time period before the event start time and the second time period after the event end time; The first image data stream and the second image data stream are determined as the target image data stream corresponding to the target feature value transfer event, and the target image data stream includes multiple ordered target images; The process by which the target IoT terminal enables the recording service is as follows: Enable the recording service based on the recording service enable settings command; or... When the actual scenario for feature value transfer is detected to meet abnormal conditions, the recording service is automatically started. The abnormal conditions include the number of objects for feature value transfer being greater than or equal to a preset number or the state of the objects for feature value transfer being abnormal. The preset number is greater than or equal to 2.

6. The method according to claim 5, characterized in that, The storage of the target data stream file includes: Extract the target event identifier from the target data stream file as a file index; The target data stream file is stored according to the file index.

7. The method according to claim 5 or 6, characterized in that, The method further includes: If the target object grants the target data stream file access permission, the target data stream file is invoked based on the target event identifier.

8. The method according to claim 5 or 6, characterized in that, The method further includes: Obtain the setting data of the recording service; The recording service and the settings data are stored together. If updated settings data is obtained, the stored settings data is updated synchronously based on the updated settings data.

9. A data stream processing device based on eigenvalue transfer, characterized in that, The device includes: an acquisition unit, a generation unit, and a transmission unit; The acquisition unit is used to acquire the target image data stream corresponding to the target feature value transfer event when the recording service of the target IoT terminal is enabled and the target feature value transfer event is completed for the target object. The target image data stream includes multiple ordered target images. The generation unit is used to generate and store a target data stream file based on the target image data stream and the target event identifier corresponding to the target feature value transfer event. The target data stream file is used to trace the target feature value transfer event. The sending unit is used to send the target data stream file to the server; The acquisition unit is used for: The system synchronously acquires a first image data stream of the target feature value transfer event from the start time of the event to the end time of the event, and a second image data stream within a preset time period. The preset time period includes one or more of the first time period before the start time of the event and the second time period after the end time of the event. The first image data stream and the second image data stream are determined as the target image data stream; The device further includes an opening unit, the opening unit being configured to: Enable the recording service based on the enabled settings command; or... When the actual scenario for feature value transfer is detected to meet abnormal conditions, the recording service is started. The abnormal conditions include the number of objects for feature value transfer being greater than or equal to a preset number or the state of the objects for feature value transfer being abnormal.

10. The apparatus according to claim 9, characterized in that, The acquisition unit is used for: The color image data stream corresponding to the target feature value transfer event is acquired synchronously and used as the target image data stream.

11. The apparatus according to any one of claims 9-10, characterized in that, The device further includes a prompting unit, the prompting unit being configured to: The target object is notified that the target feature value transfer event has been recorded and the target data stream file has been generated; The target object is prompted that the target data stream file is in a data protection state, which indicates that the target object has authorized access to the target data stream file.

12. The apparatus according to any one of claims 9-10, characterized in that, The transmitting unit is used for: If the target IoT terminal is in an idle state, the target data stream file is sent to the server.

13. A data stream processing device based on eigenvalue transfer, characterized in that, The device includes: a receiving unit and a storage unit; The receiving unit is used to receive a target data stream file sent by the target IoT terminal. The target data stream file is generated based on the target image data stream and the target event identifier corresponding to the target feature value transfer event completed by the target object. The target data stream file is used to trace the target feature value transfer event. The target image data stream includes multiple ordered target images. The storage unit is used to store the target data stream file; The process of generating the target image data stream includes: when the target IoT terminal starts recording service, completing the target feature value transfer event for the target object, and synchronously acquiring the first image data stream of the target feature value transfer event from the event start time to the event end time and the second image data stream in a preset time period, wherein the preset time period includes one or more of the first time period before the event start time and the second time period after the event end time; The first image data stream and the second image data stream are determined as the target image data stream corresponding to the target feature value transfer event, and the target image data stream includes multiple ordered target images; The process by which the target IoT terminal enables the recording service is as follows: Enable the recording service based on the recording service enable settings command; or... When the actual scenario for feature value transfer is detected to meet abnormal conditions, the recording service is automatically started. The abnormal conditions include the number of objects for feature value transfer being greater than or equal to a preset number or the state of the objects for feature value transfer being abnormal. The preset number is greater than or equal to 2.

14. The apparatus according to claim 13, characterized in that, The storage unit is used for: Extract the target event identifier from the target data stream file as a file index; The target data stream file is stored according to the file index.

15. The apparatus according to claim 13 or 14, characterized in that, The device further includes a calling unit, the calling unit being configured to: If the target object grants the target data stream file access permission, the target data stream file is invoked based on the target event identifier.

16. The apparatus according to claim 13 or 14, characterized in that, The receiving unit is further configured to: Obtain the setting data of the recording service; The storage unit is also used for: The recording service and the settings data are stored together. The device further includes an updating unit, the updating unit being configured to: If updated settings data is obtained, the stored settings data is updated synchronously based on the updated settings data.

17. A computer device, characterized in that, The device includes a processor and a memory: The memory is used to store program code and transmit the program code to the processor; The processor is configured to execute the data stream processing method based on feature value transfer as described in any one of claims 1-8 according to the instructions in the program code.

18. A computer-readable storage medium, characterized in that, The computer-readable storage medium is used to store a computer program for executing the data stream processing method based on eigenvalue transfer as described in any one of claims 1-8.

19. A computer program product, characterized in that, It includes a computer program or instructions; when the computer program or instructions are executed by a processor, the data stream processing method based on feature value transfer as described in any one of claims 1-8 is performed.

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