Action execution method and device, equipment and storage medium

Abstract

According to the embodiment of the invention, an action execution method and device, equipment and a storage medium are provided. The method comprises the following steps: acquiring a group of reference feature representations, wherein each reference feature representation is generated based on an image corresponding to a corresponding scene; determining an image feature representation of the captured image; and in response to the image feature representation matching a target reference feature representation of the set of reference feature representations, performing a target action associated with a target scene, the target scene corresponding to the target reference feature representation. In this way, according to the embodiment of the invention, the execution of the corresponding action can be triggered based on the matching of the feature representation, so that the cost of scene recognition is reduced.

Description

Technical Field

[0001] Example embodiments of the present disclosure generally relate to the field of data processing, and more particularly, to action execution methods, apparatuses, devices, and computer-readable storage media. Background Art

[0002] Images are increasingly used in various fields. However, faced with a vast amount of images, some images need to be applied while others do not. In other words, some images need to have preset actions executed on them, while others do not. Finding a suitable method to determine whether an image needs to have preset actions executed is a key issue. Summary of the Invention

[0003] In a first aspect of the present disclosure, a method for controlling the execution of an action is provided. The method comprises: obtaining a set of reference feature representations, wherein each reference feature representation is generated based on an image corresponding to a corresponding scene; determining an image feature representation of a captured image; and, in response to the image feature representation matching a target reference feature representation in the set of reference feature representations, executing a target action associated with a target scene corresponding to the target reference feature representation.

[0004] In a second aspect of the present disclosure, a device for controlling the execution of an action is provided. The device includes: an acquisition module configured to acquire a set of reference feature representations, wherein each reference feature representation is generated based on an image corresponding to a corresponding scene; a determination module configured to determine an image feature representation of a captured image; and an execution module configured to execute a target action associated with a target scene in response to the image feature representation matching a target reference feature representation in the set of reference feature representations, the target scene corresponding to the target reference feature representation.

[0005] In a third aspect of the present disclosure, an electronic device is provided. The device includes at least one processing unit; and at least one memory coupled to the at least one processing unit and storing instructions for execution by the at least one processing unit. When executed by the at least one processing unit, the instructions cause the device to perform the method of the first aspect.

[0006] In a fourth aspect of the present disclosure, a computer-readable storage medium is provided, wherein a computer program is stored on the computer-readable storage medium, and the computer program can be executed by a processor to implement the method of the first aspect.

[0007] It should be understood that the content described in this summary section is not intended to limit the key features or important features of the embodiments of the present disclosure, nor is it intended to limit the scope of the present disclosure. Other features of the present disclosure will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] The above and other features, advantages and aspects of the embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. In the accompanying drawings, the same or similar reference numerals represent the same or similar elements, wherein:

[0009] Figure 1 A schematic diagram illustrating an example environment in which embodiments of the present disclosure can be implemented;

[0010] Figure 2 A flowchart illustrating a process for controlling the execution of an action according to some embodiments of the present disclosure is shown;

[0011] Figure 3 A schematic diagram illustrating an example process of executing a control action according to some embodiments of the present disclosure;

[0012] Figure 4 shows a schematic structural block diagram of an apparatus for controlling action execution according to certain embodiments of the present disclosure;

[0013] Figure 5 A block diagram of an electronic device capable of implementing various embodiments of the present disclosure is shown. DETAILED DESCRIPTION

[0014] The following describes embodiments of the present disclosure in more detail with reference to the accompanying drawings. Although certain embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as limited to the embodiments described herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are for illustrative purposes only and are not intended to limit the scope of protection of the present disclosure.

[0015] It should be noted that the titles of any section / subsection provided herein are not limiting. Various embodiments are described throughout this document, and any type of embodiment may be included under any section / subsection. Furthermore, the embodiments described in any section / subsection may be combined in any manner with any other embodiments described in the same section / subsection and / or in different sections / subsections.

[0016] In the description of the embodiments of the present disclosure, the term "comprising" and its conjugations should be understood as open-ended, i.e., "including but not limited to". The term "based on" should be understood as "based at least in part on". The term "one embodiment" or "an embodiment" should be understood as "at least one embodiment". The term "some embodiments" should be understood as "at least some embodiments". The following description can also include other explicit and implicit definitions. The terms "first", "second", etc. can refer to different or the same objects. The following description can also include other explicit and implicit definitions.

[0017] The embodiments of the present disclosure can involve data of users, acquisition and / or use of data, etc. These aspects all comply with the corresponding laws and regulations and relevant provisions. In the embodiments of the present disclosure, all data collection, acquisition, processing, processing, forwarding, use, etc. are carried out on the premise that the user is aware of and confirms. Accordingly, when implementing the embodiments of the present disclosure, the type of data or information that can be involved, the use range, the use scenario, etc. should be notified to the user and the authorization of the user should be obtained through appropriate means according to the relevant laws and regulations. The specific notification and / or authorization method can vary according to the actual situation and application scenario, and the scope of the present disclosure is not limited in this respect.

[0018] In the present specification and embodiments, if personal information processing is involved, it will be processed on the premise of legality (for example, obtaining the consent of the subject of personal information, or being necessary for the performance of a contract, etc.), and only within the prescribed or agreed range. The user refuses to process personal information other than the necessary information required for the basic function, which does not affect the user's use of the basic function.

[0019] Conventionally, an electronic device can preset a series of rules, and when a to-be-processed image satisfies the series of rules, the electronic device can perform a preset action associated with the to-be-processed image. For the judgment of some uncommon scenes or uncommon targets, the adaptability of this implementation is poor, and the complexity of the preset rules is high, and the maintainability is low. In addition, for some specific needs, this implementation often needs to manually update the preset series of rules, and the flexibility is also low.

[0020] Embodiments of the present disclosure provide a scheme for controlling action execution. According to the scheme, a set of reference feature representations can be obtained, where each reference feature representation is generated based on an image corresponding to a respective scene. Further, an image feature representation of a photographed image can be determined. Additionally, in response to the image feature representation matching a target reference feature representation in the set of reference feature representations, a target action associated with a target scene corresponding to the target reference feature representation is executed.

[0021] Therefore, the present disclosure does not require the configuration of corresponding scene recognition rules on the electronic device side, and can trigger the execution of corresponding actions through the matching of feature representations. In this way, the embodiments of the present disclosure can improve the flexibility of action execution and reduce the deployment cost on the device side.

[0022] Sample Environment

[0023] Figure 1 1 shows a schematic diagram of an example environment 100 in which embodiments of the present disclosure can be implemented. Figure 1 As shown, example environment 100 may include electronic device 110 and remote device 120 .

[0024] In this example environment 100, electronic device 110 may communicate with remote device 120 to obtain a message sent by remote device 120. Such a message may include, for example, different reference feature representations corresponding to different scenes. For example, different reference feature representations may be generated based on images corresponding to different scenes.

[0025] As will be described in detail below, the electronic device 110 may determine whether to trigger the execution of a predetermined action based on such reference feature representations.

[0026] The electronic device 110 can be any type of mobile terminal, fixed terminal or portable terminal, including a vehicle-mounted terminal, a mobile phone, a desktop computer, a laptop computer, a notebook computer, a netbook computer, a tablet computer, a media computer, a multimedia tablet, a handheld computer, a portable game terminal, a VR / AR device, a personal communication system (PCS) device, a personal navigation device, a personal digital assistant (PDA), an audio / video player, a digital camera / camcorder, a positioning device, a television receiver, a radio broadcast receiver, an e-book device, a game device or any combination of the foregoing, including accessories and peripherals of these devices or any combination thereof. In some embodiments, the electronic device 110 can also support any type of interface for the user (such as a "wearable" circuit, etc.). In some examples, the electronic device 110 can be deployed in a vehicle, for example.

[0027] The remote device 120 can be a standalone physical remote device, a cluster of remote devices or a distributed system composed of multiple physical remote devices, a cloud remote device providing cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content distribution networks, and big data and artificial intelligence platforms, and the like basic cloud computing services. The remote device 120 may, for example, include a computing system / remote device such as a mainframe, an edge computing node, a computing device in a cloud environment, and the like.

[0028] A communication connection can be established between the remote device 120 and the electronic device 110. The communication connection can be established by wired or wireless means. The communication connection can include, but is not limited to, a Bluetooth connection, a mobile network connection, a Universal Serial Bus (USB) connection, a Wireless Fidelity (WiFi) connection, and the like, and embodiments of the present disclosure are not limited in this regard. In embodiments of the present disclosure, the remote device 120 and the electronic device 110 can achieve signaling interaction through the communication connection therebetween.

[0029] It should be understood that the structure and function of the various elements in the environment 100 are described for illustrative purposes only, without implying any limitation on the scope of the present disclosure.

[0030] Some example embodiments of the present disclosure will be described below with continued reference to the accompanying drawings.

[0031] Example Process

[0032] Figure 2 A flowchart of an example interaction process 200 according to some embodiments of the present disclosure is shown. The process 200 can be implemented at the electronic device 110. The process 200 will be described below with reference to Figure 1 .

[0033] As shown in Figure 2 , at block 210, the electronic device 110 obtains a set of reference feature representations, where each reference feature representation is generated based on an image corresponding to a respective scene.

[0034] In some embodiments, the electronic device 110 may, for example, obtain such a set of reference feature representations from the remote device 120. For example, the remote device 120 can generate corresponding feature vectors based on images corresponding to different scenes as reference feature representations. For example, the remote device 120 can utilize a neural network to encode the images to determine the corresponding feature vectors. It should be understood that such a neural network may, for example, include but is not limited to any appropriate network model such as a convolutional neural network, and the like.

[0035] In some embodiments, the remote device 120 may manage different reference feature representations corresponding to different scenarios. For example, such scenarios may correspond to different traffic scenarios. For example, such reference feature representations may include feature vectors generated based on images corresponding to different traffic scenarios.

[0036] In some embodiments, the message sent by the remote device 120 to the electronic device 110 may further include description information associated with the corresponding reference feature vector. For example, such description information may include scene information associated with the corresponding reference feature vector, such as "intersection at night".

[0037] In some other embodiments, the message sent by the remote device 120 to the electronic device 110 may further include a trigger condition associated with the corresponding reference feature vector. As will be described in detail below, such a trigger condition may, for example, indicate a similarity threshold that triggers the execution of a corresponding action.

[0038] At block 220 , the electronic device 110 determines an image feature representation of the captured image.

[0039] As an example, the electronic device 110 may acquire captured images. In one example, the electronic device 110 may be deployed in a vehicle, for example, and may acquire images captured by a camera mounted on the vehicle, for example, a real-time video stream.

[0040] Furthermore, the electronic device 110 may encode the image to determine an image feature representation of the image. For example, the electronic device 110 may process the image using a model corresponding to a neural network deployed by the remote device 120 to determine a corresponding feature vector.

[0041] At block 230 , in response to the image feature representation matching a target reference feature representation in the set of reference feature representations, the electronic device 110 performs a target action associated with a target scene corresponding to the target reference feature representation.

[0042] Specifically, the electronic device 110 may determine the similarity between the image feature representation and the set of reference feature representations. For example, the electronic device 110 may determine the cosine similarity between the feature vector of the captured image and the received reference feature vector.

[0043] Furthermore, the electronic device 110 may determine that the similarity between the image feature representation and the target reference feature representation is higher than a similarity threshold, thereby determining that the image feature representation matches the target reference feature representation.

[0044] In some embodiments, the similarity threshold may be determined based on a message received from the remote device 120. As an example, the remote device 120 may configure different similarity thresholds for different reference feature representations, thereby managing the triggering of actions more flexibly.

[0045] Further, when it is determined that the image feature representation matches the target reference feature representation, the electronic device 110 may perform a target action corresponding to the corresponding scene.

[0046] In an example where the electronic device 110 is deployed in a vehicle, such a target action may include controlling the vehicle to perform any appropriate action, such as slowing down, turning on or off components of the vehicle, controlling the vehicle to issue an alert, and the like.

[0047] In some embodiments, the target action may further include sending a message about the captured image to the remote device 120. In some examples, the message may at least indicate an image feature representation of the captured image, such as a feature vector of the image.

[0048] Additionally, such a message may also indicate status information associated with the electronic device. Continuing with the example of the electronic device 110 being deployed in a vehicle, such status information may include vehicle status information, such as the vehicle's speed, position, acceleration, and the like.

[0049] In this way, embodiments of the present disclosure can determine whether corresponding trigger conditions are met based on received reference feature representations, and trigger the execution of actions corresponding to the corresponding scenarios. In this way, embodiments of the present disclosure do not rely on the electronic device's ability to recognize specific scenarios, thereby reducing the model deployment cost at the electronic device and increasing the flexibility of controlling the execution of actions.

[0050] In some embodiments, the electronic device 110 may also trigger the remote device 120 to update such a reference feature representation or a corresponding trigger condition based on the reporting information received from the electronic device 110 , for example.

[0051] Specifically, when the number and / or frequency of messages corresponding to the target scenario received by the remote device 120 within the first time period is higher than a first threshold, the remote device may adjust the trigger condition to increase the similarity threshold corresponding to the target action.

[0052] In another example, when the number and / or frequency of messages corresponding to the target scenario received by the remote device within a second time period is lower than a second threshold, the remote device 120 may adjust the trigger condition to lower the similarity threshold corresponding to the target action.

[0053] In some embodiments, the remote device 120 may also adjust the reference feature representation corresponding to the target scene stored in the remote device 120 based on the received image feature representation corresponding to the target scene, so that the adjusted reference feature representation can be closer to the image feature representation.

[0054] In some embodiments, the remote device 120 may periodically send such reference feature representations and corresponding trigger conditions to the electronic device 110. Additionally, the remote device 120 may dynamically add reference feature representations corresponding to more scenarios, or remove reference feature representations corresponding to existing scenarios, as needed, thereby controlling the electronic device 110 to support triggering of more scenarios, or not respond to specific scenarios.

[0055] Figure 3 A schematic diagram showing an example process of executing a control action according to some embodiments of the present disclosure is shown. Figure 3 Provide explanation.

[0056] In block 310, the remote device 120 may send a vector table to the electronic device 110. As mentioned above, such a vector table may include, for example, reference vector representations corresponding to different scenes, scene labels, and trigger conditions (eg, similarity thresholds).

[0057] At block 320 , the electronic device 110 may capture an image using, for example, a camera.

[0058] At block 330 , the electronic device 110 may, for example, utilize a feature extraction model to obtain a vector representation of the image.

[0059] In block 340 , the electronic device 110 determines the cosine similarity between the vector representation of the image and the reference vector representation in the vector table, and may determine whether the cosine similarity is above a corresponding similarity threshold, thereby determining whether the vector representation of the image matches the vector table.

[0060] At block 350 , if the image vector representation matches the vector table, the electronic device 110 performs the target action corresponding to the target scene.

[0061] Therefore, the present disclosure does not require the configuration of corresponding scene recognition rules on the electronic device side, and can trigger the execution of corresponding actions through the matching of feature representations. In this way, the embodiments of the present disclosure can improve the flexibility of action execution and reduce the deployment cost on the device side.

[0062] Example devices and equipment

[0063] The embodiments of the present disclosure also provide corresponding devices for implementing the above methods or processes. Figure 41 shows a schematic structural block diagram of an apparatus 400 for controlling the execution of an action according to certain embodiments of the present disclosure. The apparatus 400 may be implemented as or included in the electronic device 110 discussed above. The various modules / components in the apparatus 400 may be implemented by hardware, software, firmware, or any combination thereof.

[0064] like Figure 4 As shown, the device 400 includes an acquisition module 410, configured to acquire a set of reference feature representations, wherein each reference feature representation is generated based on an image corresponding to a corresponding scene; a determination module 420, configured to determine an image feature representation of the captured image; and an execution module 430, configured to execute a target action associated with a target scene in response to the image feature representation matching a target reference feature representation in a set of reference feature representations, the target scene corresponding to the target reference feature representation.

[0065] In some embodiments, the device 400 also includes a matching module configured to: determine the similarity between the image feature representation and a set of reference feature representations; and determine that the image feature representation matches the target reference feature representation in response to the similarity between the image feature representation and the target reference feature representation being higher than a similarity threshold.

[0066] In some embodiments, the acquisition module 410 is further configured to receive a target message from a remote device, the target message indicating a set of reference feature representations.

[0067] In some embodiments, the target message further indicates: description information corresponding to the corresponding scenario; and trigger conditions corresponding to the corresponding scenario.

[0068] In some embodiments, the execution module 430 is further configured to: send a second message to the remote device, the second message indicating at least the image feature representation of the captured image.

[0069] In some embodiments, the second message also indicates status information associated with the current device.

[0070] In some embodiments, the apparatus 400 further includes an updating module configured to: enable the remote device to update the trigger condition corresponding to the target action based on the second message.

[0071] In some embodiments, the update module is further configured to: in response to the number and / or frequency of messages corresponding to the target scene received by the remote device during a first time period being higher than a first threshold, cause the remote device to adjust the trigger condition to increase the similarity threshold corresponding to the target action; or in response to the number and / or frequency of messages corresponding to the target scene received by the remote device during a second time period being lower than a second threshold, cause the remote device to adjust the trigger condition to lower the similarity threshold corresponding to the target action.

[0072] In some embodiments, the captured images include images captured by a camera mounted on a vehicle.

[0073] The units included in the device 400 can be implemented in various ways, including software, hardware, firmware, or any combination thereof. In some embodiments, one or more units can be implemented using software and / or firmware, such as machine executable instructions stored on a storage medium. In addition to or as an alternative to machine executable instructions, some or all of the units in the device 400 can be implemented at least in part by one or more hardware logic components. By way of example and not limitation, exemplary types of hardware logic components that can be used include field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chip (SOCs), complex programmable logic devices (CPLDs), and the like.

[0074] Figure 5 1 shows a block diagram of an electronic device 500 in which one or more embodiments of the present disclosure may be implemented. Figure 5 The illustrated electronic device 500 is merely exemplary and should not be construed as limiting the functionality and scope of the embodiments described herein. Figure 5 The electronic device 500 shown can be used to implement Figure 1 An electronic device 110 is shown.

[0075] like Figure 5 As shown, electronic device 500 is in the form of a general electronic device. Components of electronic device 500 may include, but are not limited to, one or more processors or processing units 510, memory 520, storage device 530, one or more communication units 540, one or more input devices 550, and one or more output devices 560. Processing unit 510 may be a real or virtual processor and is capable of performing various processes according to programs stored in memory 520. In a multi-processor system, multiple processing units execute computer-executable instructions in parallel to increase the parallel processing capabilities of electronic device 500.

[0076] The electronic device 500 typically includes a plurality of computer storage media. Such media can be any accessible media that can be obtained by the electronic device 500, including but not limited to volatile and non-volatile media, removable and non-removable media. The memory 520 can be a volatile memory (e.g., a register, a cache, a random access memory (RAM)), a non-volatile memory (e.g., a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), flash memory), or some combination thereof. The storage device 530 can be a removable or non-removable medium and can include a machine-readable medium, such as a flash drive, a disk, or any other medium that can be used to store information and / or data (e.g., training data for training) and can be accessed within the electronic device 500.

[0077] The electronic device 500 may further include additional removable / non-removable, volatile / non-volatile storage media. Figure 5 As shown in FIG, a magnetic disk drive for reading from or writing to a removable, non-volatile magnetic disk (e.g., a "floppy disk") and an optical disk drive for reading from or writing to a removable, non-volatile optical disk may be provided. In these cases, each drive may be connected to a bus (not shown) by one or more data media interfaces. Memory 520 may include a computer program product 525 having one or more program modules configured to perform various methods or actions of various embodiments of the present disclosure.

[0078] The communication unit 540 enables communication with other electronic devices via a communication medium. Additionally, the functions of the components of the electronic device 500 can be implemented in a single computing cluster or multiple computing machines that can communicate via a communication connection. Thus, the electronic device 500 can operate in a networked environment using a logical connection with one or more other servers, a network personal computer (PC), or another network node.

[0079] Input device 550 may be one or more input devices, such as a mouse, keyboard, or trackball. Output device 560 may be one or more output devices, such as a display, a speaker, or a printer. Electronic device 500 may also communicate with one or more external devices (not shown) via communication unit 540 as needed, such as a storage device, a display device, or the like, with one or more devices that allow a user to interact with electronic device 500, or with any device that allows electronic device 500 to communicate with one or more other electronic devices (e.g., a network card, a modem, etc.). Such communication may be performed via an input / output (I / O) interface (not shown).

[0080] According to an example implementation of the present disclosure, a computer readable storage medium is provided having computer executable instructions stored thereon, where the computer executable instructions are executed by a processor to implement the method described above. According to an example implementation of the present disclosure, a computer program product is also provided that is tangibly stored on a non-transitory computer readable medium and includes computer executable instructions, where the computer executable instructions are executed by a processor to implement the method described above.

[0081] The computer readable program instructions can also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable apparatus or other device to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions / acts specified in the flowchart and / or block diagram block or blocks.

[0082] The computer readable program instructions can also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable apparatus or other device to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions / acts specified in the flowchart and / or block diagram block or blocks.

[0083] The computer readable program instructions can also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable apparatus or other device to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions / acts specified in the flowchart and / or block diagram block or blocks.

[0084] The computer program product of the present disclosure can have a signal including said computer program. This signal can be electronic, electromagnetic, optical, or any other suitable type of signal. Such a signal can be provided through a communication connection, such as electrical wiring, optical fiber, wireless interface, etc. Examples of computer program products include computer program implemented on a personal computer, server, or other networked device. A non-transitory computer readable medium, such as a floppy disk, CD-ROM, DVD-ROM, Blu-ray Disc, hard disk, or memory stick, can also be used to implement the present disclosure. The computer program product of the present disclosure can also be provided as a service to download and use the computer program over a network, such as the Internet.

[0085] The implementations of the disclosure have been described above with the intent to be illustrative rather than limiting. Although the implementations of the disclosure have been described with regard to one or more implementations, numerous modifications and changes can be made to the implementations of the disclosure by those skilled in the art without departing from the scope and spirit of the implementations. For example, the implementations of the disclosure can be used in a variety of different applications and environments and are not limited to the specific examples described above. It is therefore intended that the disclosure not be limited to the described implementations, but that the full scope of the implementations be determined by the following claims, and their equivalents.

Claims

1. A method for controlling the execution of an action, comprising: Obtaining a set of reference feature representations, wherein each reference feature representation is generated based on an image corresponding to a corresponding scene; determining an image feature representation of the captured image; as well as In response to the image feature representation matching a target reference feature representation in the set of reference feature representations, a target action associated with a target scene corresponding to the target reference feature representation is performed.

2. The method according to claim 1, further comprising: determining a similarity between the image feature representation and the set of reference feature representations; as well as In response to the similarity between the image feature representation and the target reference feature representation being higher than a similarity threshold, it is determined that the image feature representation matches the target reference feature representation.

3. The method of claim 1 , wherein obtaining a set of reference feature representations comprises: A target message is received from a remote device, the target message indicating the set of reference feature representations.

4. The method according to claim 3, wherein the target message further indicates: Descriptive information corresponding to the corresponding scene; The trigger condition corresponding to the corresponding scenario.

5. The method of claim 1 , wherein performing a target action associated with a target scenario comprises: A second message is sent to a remote device, the second message indicating at least the image characteristic representation of the captured image. The method of claim 5 , wherein the second message further indicates status information associated with the current device.

7. The method according to claim 5, further comprising: The remote device is enabled to update a trigger condition corresponding to the target action based on the second message.

8. The method according to claim 7, wherein causing the remote device to update the trigger condition corresponding to the target action based on the second message comprises: In response to the number and / or frequency of messages corresponding to the target scenario received by the remote device within a first time period being higher than a first threshold, causing the remote device to adjust the trigger condition to increase the similarity threshold corresponding to the target action; or In response to the number and / or frequency of messages corresponding to the target scenario received by the remote device within a second time period being lower than a second threshold, the remote device adjusts the trigger condition to lower the similarity threshold corresponding to the target action.

9. The method of claim 1, wherein the captured image comprises an image captured by a camera mounted on a vehicle.

10. A device for controlling the execution of an action, comprising: an acquisition module configured to acquire a set of reference feature representations, wherein each reference feature representation is generated based on an image corresponding to a corresponding scene; a determination module configured to determine an image feature representation of the captured image; as well as An execution module is configured to execute a target action associated with a target scene in response to the image feature representation matching a target reference feature representation in the set of reference feature representations, the target scene corresponding to the target reference feature representation.

11. An electronic device comprising: at least one processing unit; as well as At least one memory coupled to the at least one processing unit and storing instructions for execution by the at least one processing unit, the instructions causing the electronic device to perform the method according to any one of claims 1 to 9 when executed by the at least one processing unit.

12. A computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the method according to any one of claims 1 to 9 is implemented.

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