Image acquisition system

Abstract

The application discloses an image acquisition system, and relates to the technical field of head-mounted devices. The image acquisition system comprises a head-mounted device and a processing device. The head-mounted device is used for acquiring at least one first image containing a shooting object, and transmitting the first image to the processing device to perform an image optimization operation on the processing device. The processing device is used for receiving the first image sent by the head-mounted device, performing the image optimization operation based on the first image to obtain a second image, and storing the second image. The image optimization operation comprises at least one of a beautifying operation, a high dynamic range optimization operation and a lens distortion correction optimization operation. Based on the image acquisition system, the power consumption of the head-mounted device image processing can be reduced.

Description

Technical Field

[0001] This application relates to the field of head-mounted display technology, and more specifically, to an image acquisition system. Background Technology

[0002] To meet the demands of immersive experiences, an increasing number of head-mounted devices now support image capture functionality.

[0003] However, due to the typical requirement for head-mounted devices to be small and lightweight, their batteries cannot be designed to be very large. Therefore, reducing the power consumption of head-mounted devices during image acquisition has become a pressing technical problem. Summary of the Invention

[0004] One objective of this application is to provide a new technical solution for image acquisition.

[0005] According to a first aspect of this application, an image acquisition system is provided, comprising:

[0006] A head-mounted device for acquiring at least one frame of a first image containing a subject, and transmitting the first image to a processing device to perform an image optimization operation on the processing device;

[0007] The processing device is configured to receive the first image sent by the head-mounted device, perform the image optimization operation based on the first image to obtain a second image, and store the second image. The image optimization operation includes at least one of beautification operation, high dynamic range optimization operation, and lens distortion correction optimization operation.

[0008] Optionally, acquiring at least one frame of the first image containing the subject includes:

[0009] Acquire at least one third image containing the subject being photographed;

[0010] For any frame of the third image, perform an image compression operation on the third image to obtain the first image corresponding to the third image;

[0011] The step of performing image optimization operations based on the first image to obtain a second image includes:

[0012] Perform image decompression on the first image to obtain the fourth image;

[0013] An image optimization operation is performed on the fourth image to obtain the second image.

[0014] Optionally, the third image is in YUV format.

[0015] Optionally, the head-mounted device supports a high dynamic range shooting mode, and acquiring at least one first frame containing the subject includes:

[0016] In preview mode, the system determines whether to activate high dynamic range shooting mode based on the brightness of the captured fifth frames.

[0017] When the high dynamic range shooting mode is activated, the first image is acquired in a first number of frames containing the subject.

[0018] Optionally, acquiring at least one frame of the first image containing the subject includes:

[0019] In preview mode, check whether the exposure and color balance parameters converge;

[0020] The first image is acquired when the exposure parameters and color balance parameters converge.

[0021] Optionally, the head-mounted device is further configured to extract image feature information of the first image and transmit the image feature information to the processing device while transmitting the first image;

[0022] The processing device is further configured to receive the image feature information sent by the head-mounted device, and perform image optimization operations based on the image feature information and the first image to obtain the second image.

[0023] Optionally, the image feature information includes at least one of image identifier, image exposure, image sensitivity, and facial information in the image.

[0024] Optionally, the image optimization operation includes a beautification operation, and the step of performing the image optimization operation based on the image feature information and the first image includes:

[0025] The face region is extracted from the first image based on the image feature information, and a beautification operation is performed on the face region to obtain the second image.

[0026] Optionally, the image optimization operation includes a high dynamic range optimization operation, and the acquisition of at least one first frame containing the subject includes:

[0027] Acquire the first image containing a first number of frames of the subject being photographed;

[0028] The step of performing image optimization operations based on the image feature information and the first image to obtain the second image includes:

[0029] Based on the image feature information and the first image of the first number of frames, a target image of the second number of frames is determined, wherein the first number is greater than or equal to the second number;

[0030] The target images of the second number of frames are fused together to obtain the second image.

[0031] Optionally, acquiring at least one frame of the first image containing the subject includes:

[0032] Upon receiving a shooting instruction from the processing device, the first image is acquired; or,

[0033] Upon receiving a shooting command triggered by the user via the shooting function button or voice on the head-mounted device, the first image is acquired;

[0034] The shooting command is used to instruct the use of a head-mounted device to capture images.

[0035] This application provides an image acquisition system, comprising: a head-mounted device for acquiring at least one frame of a first image containing a subject, transmitting the first image to a processing device for performing image optimization operations; and a processing device for receiving the first image transmitted by the head-mounted device, performing image optimization operations based on the first image to obtain a second image, and storing the second image. The image optimization operations include at least one of beautification operations, high dynamic range optimization operations, and lens distortion correction optimization operations. Based on the image acquisition system provided by this application, the power consumption of image processing in the head-mounted device can be reduced.

[0036] Other features and advantages of this application will become clear from the following detailed description of exemplary embodiments with reference to the accompanying drawings. Attached Figure Description

[0037] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments of the present application and, together with their description, serve to explain the principles of the present application.

[0038] Figure 1 This is a schematic diagram of the structure of an image acquisition system provided in this application;

[0039] Figure 2 This is a flowchart of the execution steps of a head-mounted device in an image acquisition system provided in this application;

[0040] Figure 3 This is a flowchart of the processing device execution steps in an image acquisition system provided in this application. Detailed Implementation

[0041] Various exemplary embodiments of the present application will now be described in detail with reference to the accompanying drawings. It should be noted that, unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps set forth in these embodiments do not limit the scope of the present application.

[0042] The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the scope of this application and its application or use.

[0043] Techniques, methods, and equipment known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques, methods, and equipment should be considered part of the specification.

[0044] In all the examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limitations. Therefore, other examples of exemplary embodiments may have different values.

[0045] It should be noted that similar labels and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be discussed further in subsequent figures.

[0046] This application provides an image acquisition system 100, applied to photography scenarios. For example... Figure 1 As shown, the device includes a head-mounted device 120 and a processing device 110. The head-mounted device 120 can be an AR device, a MR device, or a VR device, etc. The head-mounted device 120 can be an all-in-one head-mounted device or a split-type head-mounted device. The processing device 110 can be a terminal or a server. The terminal can be a smartphone, laptop, tablet, PDA, etc. If the head-mounted device 120 is a split-type head-mounted device, the terminal can also be a control device for the split-type head-mounted device, such as a Puck device. The server can be a cloud server, etc. It is understood that the processing device 110 has image processing capabilities, and the image processing performance of the processing device 110 is superior to that of the head-mounted device 120.

[0047] For the head-mounted device 120 in the image acquisition system, such as Figure 2 As shown, it is used to perform the following steps S210 to S220.

[0048] Step S210: Acquire at least one first image containing the subject being photographed.

[0049] In this embodiment, the user wears a head-mounted device 120 to photograph the desired object in the surrounding environment. The image acquisition device in the head-mounted device 120 acquires an image of the object, obtaining a first image. The first image reflects visual information about the user's environment, including objects, people, background, lighting conditions, etc.

[0050] The first image can be the original image captured from the user's first-person perspective, or it can be an image after basic image processing. The power consumption of the basic image processing is less than a set power consumption; basic image processing includes, for example, image compression.

[0051] Step S220: The first image is transmitted to the processing device to perform an image optimization operation on the processing device.

[0052] In this embodiment, the image optimization operation includes at least one of beautification operation, high dynamic range optimization (HDR) operation, and lens distortion correction optimization (LDC) operation.

[0053] The first image can be one frame or multiple frames. Image optimization operations can be performed on a single frame of the first image or on multiple frames of the first image. For example, high dynamic range optimization operations can be performed on multiple frames of the first image.

[0054] The head-mounted device 120 is communicatively connected to the processing device 110, and the head-mounted device 120 transmits a first image to the processing device 110 based on this communication connection. In one example, the communication connection can be one of a USB connection, a Bluetooth connection, or a Wi-Fi connection. Preferably, the communication connection is a Wi-Fi connection, which allows for faster transmission speeds.

[0055] By breaking down the entire image-taking process and delegating image optimization to the processing device, the head-mounted device only needs to acquire the original image or perform basic image processing on the original image with low power consumption, thus reducing the power consumption of the head-mounted device during image processing.

[0056] In one embodiment of this application, a single image with a large data size, such as a 4032*3024 YUV format image, occupies approximately 17MB of memory. This not only consumes a significant amount of memory and local storage in the head-mounted device but also significantly impacts its transmission efficiency. Therefore, to improve image transmission efficiency and reduce power consumption during image transmission, step S210 can be specifically implemented through steps S2101 to S2102. That is, the head-mounted device 120 is specifically used to execute steps S2101 to S2102.

[0057] Step S2101: Acquire at least one third image containing the subject being photographed.

[0058] In this embodiment, the third image can be in at least one of RAW, RGB, and YUV formats. Using YUV format for the third image is more advantageous for adjusting exposure and color balance parameters in preview mode of the image acquisition device within the head-mounted device.

[0059] Step S2102: For any frame of the third image, perform an image compression operation on the third image to obtain the first image corresponding to the third image.

[0060] In this embodiment, when the image optimization operation is a high dynamic range optimization operation, a first number of third images with different exposures are acquired. For any frame of the third image, an image compression operation is performed on the third image to obtain a first image corresponding to the third image in the first number of frames.

[0061] In one example, the first image can be in HEIC format. A 17MB image will be compressed to between 2MB and 3MB, while ensuring minimal loss of image content and no impact on subsequent use.

[0062] When the third image is in YUV format, in the same scene, the image obtained using the original YUV optimization algorithm and the image obtained by performing image optimization after compression in this solution have a SSIM (Structural Similarity) of more than 0.91, which is difficult for the human eye to distinguish.

[0063] By performing compression on the acquired third image, the file size can be reduced, the image transmission speed can be increased, and the power consumption during transmission can be reduced while minimizing image quality loss.

[0064] In one embodiment of this application, the head-mounted device supports both high dynamic range shooting mode and preview mode. Step S210 can be specifically implemented through steps S2103 to S2104 described below. That is, the head-mounted device 120 is specifically used to execute steps S2103 to S2104.

[0065] Step S2103: In preview mode, determine whether to activate high dynamic range shooting mode based on the brightness of the acquired multi-frame fifth images.

[0066] In this embodiment, the preview mode is a mode in which the image is displayed through the viewfinder or LCD screen of the image acquisition device before the user presses the shutter button. In preview mode, the system automatically detects whether the conditions for activating the high dynamic range shooting mode are met based on the brightness of the acquired multi-frame fifth images, eliminating the need for manual configuration of the high dynamic range shooting mode by the user.

[0067] If the conditions for activating High Dynamic Range (HDR) shooting mode are met, then HDR shooting mode will be activated. If the conditions for activating HDR shooting mode are not met, then HDR shooting mode does not need to be activated.

[0068] Step S2104: When the high dynamic range shooting mode is activated, acquire a first image containing a first number of frames of the subject.

[0069] When the high dynamic range (HDR) shooting mode is activated, a first image containing a first number of frames of the subject is acquired. If the conditions for activating HDR shooting mode are not met, it is not necessary to activate HDR shooting mode; only a single frame containing the subject needs to be acquired. This reduces the power consumption generated during image acquisition by the head-mounted device.

[0070] In one embodiment of this application, the head-mounted device 120 needs to ensure that the captured photos have appropriate exposure and color balance. Step S210 can be specifically implemented through steps S2105 to S2106 described below. That is, the head-mounted device 120 is specifically used to perform steps S2105 to S2106.

[0071] Step S2105: In preview mode, check whether the exposure parameters and color balance parameters converge.

[0072] In this embodiment, the exposure parameters include automatic exposure (AE) parameters, and the color balance parameters include automatic white balance (AWB) parameters.

[0073] Automatic exposure parameters refer to the automatic adjustment of exposure parameters by the image acquisition device to ensure that the captured image has appropriate brightness. Automatic adjustment of exposure parameters includes, for example, automatically adjusting the aperture, shutter speed, and ISO. The goal of automatic exposure is to make the image brightness approximate the brightness of the scene as perceived by the human eye. The image acquisition device measures the brightness of the scene and automatically adjusts the aperture, shutter speed, and ISO to achieve a suitable exposure level. In preview mode, the image acquisition device needs to continuously adjust the exposure parameters until a suitable exposure value is found. This process is called automatic exposure parameter convergence.

[0074] Automatic white balance parameters refer to the automatic adjustment of color balance by the image acquisition device to ensure that the captured image has natural colors under different lighting conditions. The goal of automatic white balance is to ensure that white objects in the image appear white under different lighting conditions. The image acquisition device automatically adjusts the color balance parameters by measuring the colors in the scene to eliminate color cast. In preview mode, the image acquisition device needs to continuously adjust the color balance parameters until a suitable balance point is found. This process is called automatic white balance parameter convergence.

[0075] Step S2106: Acquire the first image when the exposure parameters and color balance parameters converge.

[0076] The first image is acquired only when the exposure and color balance parameters converge. If the exposure and color balance parameters do not converge, there is no need to acquire the first image, thus ensuring the quality of the acquired first image.

[0077] In one embodiment of this application, step S2106 may specifically include step S21061: acquiring a first image of a first number of frames when the exposure parameters and color balance parameters converge and the high dynamic range shooting mode is activated. This ensures the quality of the first image of the first number of frames acquired, thereby ensuring the quality of the image after the high dynamic range optimization operation.

[0078] In one embodiment of this application, the head-mounted device 120 is also used to perform the following steps S230 to S240.

[0079] Step S230: Extract image feature information from the first image.

[0080] In this embodiment, the image feature information includes at least one of image identifier, image exposure, image sensitivity, and facial information in the image. The image identifier may be, for example, the image name. The facial information in the image may be, for example, the location information of a facial region.

[0081] Step S240: In the case of transmitting the first image, the image feature information of the first image is transmitted to the processing device.

[0082] In this embodiment, the first image and its image feature information can be associated and stored, and the association relationship can be transmitted to the processing device 110 so that the processing device 110 can find the first image based on the association relationship, and then perform image optimization operation based on the first image to obtain the second image.

[0083] In one example, the processing device 110 can find a first image associated with an image identifier in the image feature information, and then perform an image optimization operation based on the first image to obtain a second image.

[0084] Finding the first image based on image feature information can speed up the search for the first image and improve image processing speed.

[0085] In one embodiment of this application, the head-mounted device 120 is also used to perform the following steps S250 to S260.

[0086] Step S250: Extract image feature information from the third image.

[0087] In this embodiment, the image feature information includes at least one of image identifier, image exposure, image sensitivity, and facial information in the image. The image identifier may be, for example, the image name. The facial information in the image may be, for example, the location information of a facial region.

[0088] Step S260: While transmitting the first image, transmit the image feature information of the third image to the processing device.

[0089] In this embodiment, the image feature information of the first image and the third image can be associated and stored, and the association relationship can be transmitted to the processing device 110 so that the processing device 110 can find the first image according to the association relationship, and then perform image optimization operation based on the first image to obtain the second image.

[0090] Since the third image is the original image, its image features are more accurate. By associating and storing the image features of the first image and the third image, this association can be used to find the first image. This improves the accuracy of finding the first image.

[0091] In one embodiment of this application, step S210 may specifically include step S270 or step S280.

[0092] Step S270: Upon receiving a shooting instruction sent by the processing device, acquire the first image.

[0093] In one example, the shooting instruction is a command by which the user configures the processing device to capture images using the head-mounted device.

[0094] Step S280: Upon receiving a shooting command triggered by the user via the head-mounted device's shooting function button or voice, acquire the first image.

[0095] In this embodiment, the shooting command is used to instruct the use of a head-mounted device to capture images.

[0096] The first image is acquired only upon receiving a shooting command, which reduces unnecessary power consumption of the head-mounted device.

[0097] Regarding the processing device 110 in the image acquisition system provided in this application, such as Figure 3 As shown, it is used to perform the following steps S310 to S330.

[0098] Step S310: Receive the first image sent by the head-mounted device.

[0099] Step S320: Perform image optimization operation based on the first image to obtain the second image.

[0100] In this embodiment, the image optimization operation includes at least one of beautification operation, high dynamic range optimization operation, and lens distortion correction optimization operation.

[0101] Step S330: Store the second image.

[0102] In this embodiment, the processing device 110 can deploy an application corresponding to the head-mounted device 120. Steps S310 to S330 described above are executed in this application. Similarly, a second image can be displayed in this application. This does not affect the use of the processing device's own image acquisition function.

[0103] Image optimization is performed on the processing device 110 side, thus avoiding image optimization on the head-mounted device 120 and reducing the power consumption of the head-mounted device 120. Furthermore, storage is performed on the processing device 110 side, facilitating viewing of the optimized second image on the processing device 110 side and reducing the memory usage of the head-mounted device 120.

[0104] This application provides an image acquisition system, comprising: a head-mounted device for acquiring at least one frame of a first image containing a subject, transmitting the first image to a processing device for performing image optimization operations; and a processing device for receiving the first image sent by the head-mounted device, performing image optimization operations based on the first image to obtain a second image, and storing the second image. The image optimization operations include at least one of beautification operations, high dynamic range optimization operations, and lens distortion correction optimization operations. Based on the image acquisition system provided by this application, the power consumption of image processing in the head-mounted device can be reduced, achieving mobile phone-like photography effects even with low performance and low power consumption of the head-mounted device.

[0105] In one embodiment of this application, the image optimization operation includes a beautification operation, and the above step S320 includes steps S3201 to S3202.

[0106] Step S3201: Extract the face region based on the first image.

[0107] Step S3202: Perform a beautification operation on the face area to obtain the second image.

[0108] In one embodiment of this application, the image optimization operation includes a high dynamic range optimization operation, and step S210 in the head-mounted device 120 includes acquiring a first image containing a first number of frames of the subject. Step S320 includes steps S3203 to S3204.

[0109] Step S3203: Based on the first image of the first number of frames, determine the target image of the second number of frames.

[0110] In this embodiment, the first quantity is greater than or equal to the second quantity.

[0111] Step S3204: Fuse the target images of the second number of frames to obtain the second image.

[0112] In one embodiment of this application, the image optimization operation includes a lens distortion correction optimization operation. The above step S320 includes using a lens distortion correction optimization algorithm to perform a lens distortion correction optimization operation based on a first image to obtain a second image.

[0113] In one example, the lens distortion correction optimization operation can be an optimization operation performed by a deep learning-based automatic distortion correction algorithm. This deep learning-based automatic distortion correction algorithm performs lens distortion and perspective distortion correction through two sub-networks (LineNet and ShapeNet), respectively.

[0114] In one embodiment of this application, in order to avoid losing image content and ensure the quality of the optimized image, the above step S320 may specifically include steps S3205 to S3206.

[0115] Step S3205: Perform image decompression on the first image to obtain the fourth image.

[0116] Step S3206: Perform image optimization operation on the fourth image to obtain the second image.

[0117] It can be understood that the image decompression operation in this embodiment is an image restoration operation, which is the opposite of the image compression operation.

[0118] In one embodiment of this application, step S3206 may specifically include extracting a face region from the fourth image, performing a beautification operation on the face region, and obtaining a second image.

[0119] In one embodiment of this application, step S3205 may specifically include performing an image decompression operation on any first image in a first number of frames to obtain a fourth image of the first number of frames. Step S3206 may specifically include determining a target image of a second number of frames from the fourth image of the first number of frames; fusing the target images of the second number of frames to obtain a second image. Wherein, the first number is greater than or equal to the second number.

[0120] In one embodiment of this application, the image optimization operation includes a lens distortion correction optimization operation. The above step S3206 includes performing a lens distortion correction optimization operation on the fourth image using a lens distortion correction optimization algorithm to obtain a second image.

[0121] In one embodiment of this application, the processing device 110 is further configured to perform the following steps S340 to S350.

[0122] Step S340: Receive image feature information of the first image sent by the head-mounted device.

[0123] Step S350: Based on the image feature information of the first image and the first image, perform image optimization operation to obtain the second image.

[0124] In one embodiment of this application, the image optimization operation includes a beautification operation. The above step S350 may specifically include: extracting the face region from the first image based on the image feature information of the first image, performing a beautification operation on the face region, and obtaining the second image.

[0125] In one embodiment of this application, the image optimization operation includes a high dynamic range optimization operation, and the above step S350 may specifically include steps S3501 to S3502.

[0126] Step S3501: Based on the image feature information of the first image and the first image of the first number of frames, determine the target image of the second number of frames.

[0127] In this embodiment, the first quantity is greater than or equal to the second quantity.

[0128] In one example, step S3501 may specifically include: selecting a target image from a first number of frames of first images based on the brightness of the first image in the image feature information of the first image. The specific frame identifier of the selected target image is the frame identifier corresponding to the target brightness required for high dynamic range optimization determined based on the brightness of the first image in the first number of frames.

[0129] Step S3502: The target images of the second number of frames are fused to obtain the second image.

[0130] Finding the target image based on the image feature information of the first image can speed up the search and improve the image processing speed.

[0131] In one embodiment of this application, the processing device 110 is further configured to perform the following steps S360 to S370.

[0132] Step S360: Receive image feature information of the third image sent by the head-mounted device.

[0133] Step S370: Locate the first image based on the image feature information of the third image.

[0134] Since the third image is the original image, its image features are more accurate. By associating and storing the image features of the first image and the third image, this association can be used to find the first image. This improves the accuracy of finding the first image.

[0135] This application may be a system, method, and / or computer program product. A computer program product may include a computer-readable storage medium having computer-readable program instructions loaded thereon for causing a processor to implement various aspects of this application.

[0136] Computer-readable storage media can be tangible devices capable of holding and storing instructions for use by an instruction execution device. Computer-readable storage media can be, for example—but not limited to—electrical storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any suitable combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital multifunction disc (DVD), memory sticks, floppy disks, mechanical encoding devices, such as punch cards or recessed protrusions storing instructions thereon, and any suitable combination thereof. The computer-readable storage media used herein are not to be construed as transient signals themselves, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., light pulses through fiber optic cables), or electrical signals transmitted through wires.

[0137] The computer-readable program instructions described herein can be downloaded from computer-readable storage media to various computing / processing devices, or downloaded via a network, such as the Internet, local area network, wide area network, and / or wireless network, to an external computer or external storage device. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards them to the computer-readable storage media in the respective computing / processing device.

[0138] The computer program instructions used to perform the operations of this application may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, etc., and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The computer-readable program instructions may be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, electronic circuits, such as programmable logic circuits, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), are personalized by utilizing state information from the computer-readable program instructions. These electronic circuits can execute the computer-readable program instructions to implement various aspects of this application.

[0139] Various aspects of this application are described herein with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-readable program instructions.

[0140] These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that, when executed by the processor of the computer or other programmable data processing apparatus, they create means for implementing the functions / actions specified in one or more blocks of the flowchart and / or block diagram. These computer-readable program instructions can also be stored in a computer-readable storage medium that causes a computer, programmable data processing apparatus, and / or other device to operate in a particular manner; thus, the computer-readable medium storing the instructions comprises an article of manufacture that includes instructions for implementing aspects of the functions / actions specified in one or more blocks of the flowchart and / or block diagram.

[0141] Computer-readable program instructions may 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 data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to perform the functions / actions specified in one or more boxes of a flowchart and / or block diagram.

[0142] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of an instruction containing one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions. It will be well known to those skilled in the art that implementation in hardware, implementation in software, and implementation using a combination of software and hardware are equivalent.

[0143] The various embodiments of this application have been described above. These descriptions are exemplary and not exhaustive, nor are they limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen to best explain the principles, practical applications, or technical improvements to the technology in the market, or to enable others skilled in the art to understand the embodiments disclosed herein. The scope of this application is defined by the appended claims.

Claims

1. An image acquisition system, characterized in that, include: A head-mounted device for acquiring at least one frame of a first image containing a subject, and transmitting the first image to a processing device to perform an image optimization operation on the processing device; The processing device is configured to receive the first image sent by the head-mounted device, perform the image optimization operation based on the first image to obtain a second image, and store the second image. The image optimization operation includes at least one of beautification operation, high dynamic range optimization operation, and lens distortion correction optimization operation.

2. The image acquisition system according to claim 1, characterized in that, The acquisition of at least one frame of a first image containing the subject being photographed includes: Acquire at least one third image containing the subject being photographed; For any frame of the third image, perform an image compression operation on the third image to obtain the first image corresponding to the third image; The step of performing image optimization operations based on the first image to obtain a second image includes: Perform image decompression on the first image to obtain the fourth image; An image optimization operation is performed on the fourth image to obtain the second image.

3. The image acquisition system according to claim 2, characterized in that, The third image is in YUV format.

4. The image acquisition system according to claim 1, characterized in that, The head-mounted device supports a high dynamic range shooting mode, and acquiring at least one first frame containing the subject includes: In preview mode, the system determines whether to activate high dynamic range shooting mode based on the brightness of the captured fifth frames. When the high dynamic range shooting mode is activated, the first image is acquired in a first number of frames containing the subject.

5. The image acquisition system according to claim 1, characterized in that, The acquisition of at least one frame of a first image containing the subject being photographed includes: In preview mode, check whether the exposure and color balance parameters converge; The first image is acquired when the exposure parameters and color balance parameters converge.

6. The image acquisition system according to claim 1, characterized in that, The head-mounted device is also used to extract image feature information of the first image, and transmit the image feature information to the processing device while transmitting the first image; The processing device is further configured to receive the image feature information sent by the head-mounted device, and perform image optimization operations based on the image feature information and the first image to obtain the second image.

7. The image acquisition system according to claim 6, characterized in that, Image feature information includes at least one of image identifier, image exposure, image sensitivity, and facial information in the image.

8. The image acquisition system according to claim 6, characterized in that, The image optimization operation includes a beautification operation. The step of performing the image optimization operation based on the image feature information and the first image includes: The face region is extracted from the first image based on the image feature information, and a beautification operation is performed on the face region to obtain the second image.

9. The image acquisition system according to claim 6, characterized in that, The image optimization operation includes a high dynamic range optimization operation, and the acquisition of at least one first image containing the subject includes: Acquire the first image containing a first number of frames of the subject being photographed; The step of performing image optimization operations based on the image feature information and the first image to obtain the second image includes: Based on the image feature information and the first image of the first number of frames, a target image of the second number of frames is determined, wherein the first number is greater than or equal to the second number; The target images of the second number of frames are fused together to obtain the second image.

10. The image acquisition system according to any one of claims 1-9, characterized in that, The acquisition of at least one frame of a first image containing the subject being photographed includes: Upon receiving a shooting instruction from the processing device, the first image is acquired; or, Upon receiving a shooting command triggered by the user via the shooting function button or voice on the head-mounted device, the first image is acquired; The shooting command is used to instruct the use of a head-mounted device to capture images.

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