WO2022134957A1 - 摄像头遮挡检测方法及系统、电子设备及存储介质 - Google Patents

摄像头遮挡检测方法及系统、电子设备及存储介质 Download PDF

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WO2022134957A1
WO2022134957A1 PCT/CN2021/131283 CN2021131283W WO2022134957A1 WO 2022134957 A1 WO2022134957 A1 WO 2022134957A1 CN 2021131283 W CN2021131283 W CN 2021131283W WO 2022134957 A1 WO2022134957 A1 WO 2022134957A1
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picture
camera
similarity
auxiliary
sub
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PCT/CN2021/131283
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English (en)
French (fr)
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高浩波
李海
班孝坤
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展讯通信（上海）有限公司
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Publication of WO2022134957A1 publication Critical patent/WO2022134957A1/zh

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
    • H04N23/60—Control of cameras or camera modules

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  • the present invention relates to the technical field of electronic devices, and in particular, to a camera occlusion detection method and system, an electronic device and a storage medium.
  • This method needs to be implemented with the help of ambient light brightness, and the statistical ambient light brightness information needs to go through the aem statistical module, but only the raw sensor has the aem statistical module, and other sensors such as the yuv sensor do not have the aem statistical module, so they cannot be obtained.
  • the brightness information of ambient light if these sensors are used as mobile phone cameras, the above judgment function cannot be realized.
  • a distance sensor or an ultrasonic sensor is installed on the back panel of the mobile phone, and the distance between the object and the camera is detected by the sensor, so as to determine whether the auxiliary camera is blocked.
  • This method requires additional sensors to be installed, which increases the cost of the phone.
  • the technical problem to be solved by the present invention is to provide a camera occlusion detection method and system, an electronic device and a storage medium in order to overcome the above-mentioned defects in the prior art.
  • a first aspect of the present invention provides a camera occlusion detection method, comprising the following steps:
  • Whether the secondary camera is blocked is determined according to the similarity between the first picture and the second picture.
  • the acquiring the first picture taken by the main camera and the second picture taken by the auxiliary camera specifically includes:
  • the pictures taken by the main camera and the auxiliary camera are preprocessed respectively to obtain a first picture and a second picture with the same field of view and the same size.
  • determining whether the auxiliary camera is blocked according to the similarity between the first picture and the second picture specifically includes:
  • the calculating the similarity between the first picture and the second picture specifically includes:
  • each first sub-picture respectively determine whether the first sub-picture is similar to the second sub-picture at the corresponding position
  • the similarity between the first picture and the second picture is calculated according to all the judged similarity results.
  • a second aspect of the present invention provides a camera occlusion detection system, including:
  • control module configured to control the main camera and the auxiliary camera to shoot in response to entering a non-single-shot shooting mode; wherein, the spatial areas captured by the main camera and the auxiliary camera are consistent;
  • an acquisition module configured to acquire the first picture taken by the main camera and the second picture taken by the auxiliary camera
  • a determination module configured to determine whether the auxiliary camera is blocked according to the similarity between the first picture and the second picture.
  • the acquiring module is specifically configured to preprocess the pictures taken by the main camera and the auxiliary camera respectively, to obtain a first picture and a second picture with the same field of view and the same size.
  • the determining module specifically includes:
  • a computing unit for computing the similarity between the first picture and the second picture
  • a determination unit configured to determine whether the similarity is lower than a preset value, and if yes, determine that the secondary camera is blocked; and if no, determine that the secondary camera is not blocked.
  • the computing unit specifically includes:
  • a cropping subunit used for cropping the first picture into several first subpictures, and for cropping the second picture into several second subpictures; wherein, the first subpicture and the second subpicture are the same size and quantity;
  • a judging subunit for each first subpicture, respectively judging whether the first subpicture is similar to the second subpicture at the corresponding position;
  • a calculation subunit configured to calculate the similarity between the first picture and the second picture according to all the similarities determined.
  • a third aspect of the present invention provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, the processor implementing the computer program as described in the first aspect when the processor executes the computer program
  • the camera occlusion detection method
  • a fourth aspect of the present invention provides a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, implements the camera occlusion detection method described in the first aspect.
  • the positive improvement effect of the present invention is: after entering the non-single-shot shooting mode, the main camera and the auxiliary camera are controlled to shoot at the same time, and the first picture taken by the main camera and the second picture taken by the auxiliary camera are determined according to the similarity. Whether the secondary camera is blocked.
  • the present invention can also realize whether the auxiliary camera is blocked without additional hardware cost or limited by a specific camera, and has higher versatility and adaptability.
  • FIG. 1 is a flowchart of a camera occlusion detection method according to Embodiment 1 of the present invention.
  • FIG. 2 is a flowchart of a specific method of step S103 provided in Embodiment 1 of the present invention.
  • FIG. 3 is an effect diagram of cropping a first picture into a first sub-picture according to Embodiment 1 of the present invention.
  • FIG. 4 is an effect diagram of cropping a second picture into a second sub-picture according to Embodiment 1 of the present invention.
  • FIG. 5 is a structural block diagram of a camera occlusion detection system according to Embodiment 2 of the present invention.
  • FIG. 6 is a schematic structural diagram of an electronic device according to Embodiment 3 of the present invention.
  • the camera occlusion detection method provided by the embodiment of the present invention can be applied to an electronic device including a main camera and an auxiliary camera.
  • the spatial areas captured by the main camera and the auxiliary camera are the same.
  • the primary camera and the secondary camera are located on the same side of the electronic device, eg, both rear cameras.
  • the number of auxiliary cameras may be one, two, or even more.
  • a camera may include photosensitive elements such as a lens group and an image sensor, wherein the lens group includes a plurality of lenses (convex or concave) for collecting light signals reflected by objects to be photographed, and transmitting the collected light signals to the image sensor.
  • the image sensor generates an original image of the object to be photographed according to the light signal.
  • the preview image displayed on the display screen is the image captured by the main camera. That is to say, if the main camera is blocked, you can directly know by viewing the preview screen. Specifically, if the preview screen is blocked, the main camera is blocked, and if the preview screen is not blocked, the main camera is not blocked. Therefore, the camera occlusion detection method provided by the embodiment of the present invention is mainly used to detect whether the auxiliary camera is occluded.
  • this embodiment provides a camera occlusion detection method, including the following steps S101-S103:
  • Step S101 in response to entering a non-single-shot shooting mode, control the main camera and the auxiliary camera to shoot.
  • the spatial areas captured by the main camera and the auxiliary camera are the same.
  • the non-single-shot shooting mode refers to shooting in a non-single-shot scene. Specifically, after entering the non-single-shot shooting mode, in response to a triggered shooting operation, use at least two cameras to shoot simultaneously to Realize different shooting functions, such as depth of field mode, optical zoom, etc.
  • the shooting operation in response to a shooting operation triggered by the user, for example, the user realizes real-time or time-lapse shooting by clicking the "shoot" icon.
  • the shooting operation in response to the system timing the shooting operation, for example, the shooting operation is performed after entering a non-single shooting shooting mode for a preset time period.
  • Step S102 Acquire a first picture taken by the main camera and a second picture taken by the auxiliary camera.
  • step S102 the pictures taken by the main camera and the auxiliary camera are preprocessed respectively to obtain a first picture and a second picture with the same field of view and the same size.
  • the main camera and the auxiliary camera on the electronic device are different, for example, the main camera and the auxiliary camera are arranged horizontally or vertically, the field of view angles of the main camera and the auxiliary camera are different.
  • the pictures taken by the main camera and the auxiliary camera are preprocessed, so that the field of view and size of the two pictures remain the same.
  • the edges of the two pictures are first cropped, and then the cropped pictures are subjected to homography matrix mapping to obtain the first picture and the second picture with the same field of view and size.
  • the ratio of the cropped picture is related to the arrangement of the primary and secondary cameras.
  • the above-mentioned preprocessing further includes: converting the pictures taken by the main camera and the auxiliary camera into single-channel grayscale images.
  • the format of the first picture and the second picture must be the same, usually in YUV format or RGB format.
  • the format of the main camera output picture is raw format
  • the format of the auxiliary camera output picture is YUV format
  • the format of the picture output by the main camera needs to be converted, that is, the raw format is converted into YUV format.
  • step S102 if only the first picture taken by the main camera can be obtained, but the second picture taken by the auxiliary camera cannot be obtained, it means that the electronic device is in a non-single-shot shooting mode It still uses a single camera, the main camera, for shooting, and does not achieve true non-single-shot shooting. In this case, there is no need to continue to perform the subsequent step S103.
  • Step S103 Determine whether the auxiliary camera is blocked according to the similarity between the first picture and the second picture.
  • step S103 specifically includes the following steps S103a-S103d:
  • Step S103a Calculate the similarity between the first picture and the second picture.
  • step S103a includes the following steps S103a1S103a3:
  • Step S103a cropping the first picture into several first sub-pictures, and cropping the second picture into several second sub-pictures; wherein the size of the first sub-picture and the second sub-picture is the sum of the Quantities are the same. The more the number of cropped sub-pictures, the more accurate the calculation of the similarity between the first picture and the second picture.
  • Step S103a2 For each first sub-picture, determine whether the first sub-picture is similar to the second sub-picture at the corresponding position.
  • the size of the first picture and the second picture are both 27*24, and the first picture is cropped into 9 first sub-pictures with a size of 9*8, as shown in Figure 3 Show. Similarly, the second picture is also cropped into 9 second sub-pictures with a size of 9*8, as shown in FIG. 4 .
  • the differential hash algorithm uses the differential hash algorithm to determine whether the first sub-picture 11 and the second sub-picture 21 at the corresponding position are similar, if the Hamming distance between the hash value of the first sub-picture 11 and the hash value of the second sub-picture 21 is less than 10, the first sub-picture 11 is considered to be similar to the second sub-picture 21, otherwise the first sub-picture 11 and the second sub-picture 21 are considered to be dissimilar.
  • Step S103a3 Calculate the similarity between the first picture and the second picture according to all the determined similarity results.
  • the default similarity is set to 1%, and there is a set of similar first sub-pictures and second sub-pictures, the similarity between the first and second pictures is increased by 11%. If there are 9 groups of similar first sub-pictures and second sub-pictures, the similarity between the first and second pictures is 100%.
  • the default similarity and the correspondingly increased similarity in the presence of a group of similar first sub-pictures and second sub-pictures may be set according to the number of the first sub-picture and the second sub-picture.
  • the first picture is cropped into a plurality of first sub-pictures
  • the second picture is cropped into a plurality of second sub-pictures to compare whether the sub-pictures are similar, and then calculate the first
  • the similarity between the picture and the second picture improves the accuracy of the similarity calculation, thereby improving the accuracy of judging whether the auxiliary camera is blocked, and improving the user experience.
  • Step S103b judging whether the similarity is lower than a preset value, if yes, execute step S103c, if not, execute step S103d.
  • the preset value can be set according to the actual situation, for example, it can be set to 90% or 80%.
  • Step S103c it is determined that the auxiliary camera is blocked.
  • a prompt message is output to prompt the user that the secondary camera is blocked.
  • the user can adjust the occluder, such as a human hand, so that the auxiliary camera is no longer occluded.
  • Step S103d it is determined that the auxiliary camera is not blocked.
  • the main camera and the auxiliary camera are controlled to shoot at the same time, and whether the auxiliary camera is blocked.
  • this embodiment does not require additional hardware cost or is limited to a specific camera, and can also determine whether the auxiliary camera is blocked, which has higher versatility and adaptability.
  • it is more accurate to judge whether the auxiliary camera is blocked according to the similarity of the pictures taken by the main and auxiliary cameras at the same time, compared with the subjective judgment of the user.
  • This embodiment provides a camera occlusion detection system 50 , as shown in FIG. 5 , including a control module 51 , an acquisition module 52 and a determination module 53 .
  • the control module 51 is configured to control the main camera and the auxiliary camera to shoot in response to entering a non-single shooting mode. Among them, the spatial areas captured by the main camera and the auxiliary camera are the same.
  • the obtaining module 52 is configured to obtain the first picture taken by the main camera and the second picture taken by the auxiliary camera.
  • the obtaining module is specifically configured to preprocess the pictures taken by the main camera and the auxiliary camera respectively, so as to obtain a first picture and a second picture with the same field of view and the same size .
  • the determining module 53 is configured to determine whether the auxiliary camera is blocked according to the similarity between the first picture and the second picture.
  • the above-mentioned determining module specifically includes:
  • a computing unit for computing the similarity between the first picture and the second picture
  • a determination unit configured to determine whether the similarity is lower than a preset value, and if yes, determine that the secondary camera is blocked; and if no, determine that the secondary camera is not blocked.
  • the above-mentioned computing unit specifically includes:
  • a cropping subunit used for cropping the first picture into several first subpictures, and for cropping the second picture into several second subpictures; wherein, the first subpicture and the second subpicture are the same size and quantity;
  • a judging subunit for each first subpicture, respectively judging whether the first subpicture is similar to the second subpicture at the corresponding position;
  • a calculation subunit configured to calculate the similarity between the first picture and the second picture according to all the similarities determined.
  • the above camera occlusion detection system may specifically be a separate chip, a chip module or a terminal, or may be a chip or a chip module integrated in the terminal.
  • each module/unit included in the camera occlusion detection system described in the above embodiments it may be a software module/unit, a hardware module/unit, or a part of a software module/unit and a part of a hardware module/unit .
  • each module/unit included therein may be implemented by hardware such as circuits, or at least some of the modules/units may be implemented by a software program.
  • Running on the processor integrated inside the chip the remaining part of the modules/units can be implemented by hardware such as circuits; for each device and product applied to or integrated in the chip module, each module/unit contained therein can be implemented using circuits, etc.
  • modules/units may be located in the same component (such as a chip, circuit module, etc.) or in different components of the chip module, or at least some of the modules/units may be implemented by a software program, and the software program runs
  • the remaining part of the modules/units can be implemented by hardware such as circuits; for each device and product applied to or integrated in the terminal, each module/unit included can be implemented by hardware such as circuits.
  • modules/units may be located in the same component (for example, a chip, circuit module, etc.) or different components in the terminal, or at least some modules/units may be implemented by software programs that run on the terminal Internally integrated processor, the remaining part of the modules/units can be implemented in hardware such as circuits.
  • FIG. 6 is a schematic structural diagram of an electronic device provided in this embodiment.
  • the electronic device includes a memory, a processor, and a computer program stored on the memory and executable on the processor, and the processor implements the camera occlusion detection method of Embodiment 1 when the processor executes the program.
  • the electronic device 3 shown in FIG. 6 is only an example, and should not impose any limitations on the function and scope of use of the embodiments of the present invention.
  • the electronic device in the embodiment of the present invention may be a mobile phone, a tablet computer, a PDA (Personal Digital Assistant), a POS (Point of Sales, a sales terminal), a vehicle terminal, a wearable device, etc., wherein the wearable device may be a smart Bracelets, smart watches, wristbands, smart glasses, necklaces, etc.
  • the components of the electronic device 3 may include, but are not limited to: the above-mentioned at least one processor 4 , the above-mentioned at least one memory 5 , and a bus 6 connecting different system components (including the memory 5 and the processor 4 ).
  • the bus 6 includes a data bus, an address bus and a control bus.
  • the memory 5 may include volatile memory, such as random access memory (RAM) 51 and/or cache memory 52 , and may further include read only memory (ROM) 53 .
  • RAM random access memory
  • ROM read only memory
  • the memory 5 may also include a program/utility 55 having a set (at least one) of program modules 54 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, which An implementation of a network environment may be included in each or some combination of the examples.
  • program modules 54 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, which An implementation of a network environment may be included in each or some combination of the examples.
  • the processor 4 executes various functional applications and data processing by running the computer program stored in the memory 5, for example, the camera occlusion detection method in Embodiment 1 of the present invention.
  • the electronic device 3 may also communicate with one or more external devices 7 (eg keyboards, pointing devices, etc.). Such communication may take place through an input/output (I/O) interface 8 . Also, the electronic device 3 may communicate with one or more networks (eg, a local area network (LAN), a wide area network (WAN), and/or a public network such as the Internet) through a network adapter 9 . As shown in FIG. 6 , the network adapter 9 communicates with other modules of the electronic device 3 through the bus 6 . It should be understood that, although not shown in FIG. 6, other hardware and/or software modules may be used in conjunction with the electronic device 3, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID (disk arrays) ) systems, tape drives, and data backup storage systems.
  • This embodiment provides a computer-readable storage medium on which a computer program is stored, and when the program is executed by a processor, implements the steps of the camera occlusion detection method of Embodiment 1.
  • the readable storage medium may include, but is not limited to, a portable disk, a hard disk, a random access memory, a read-only memory, an erasable programmable read-only memory, an optical storage device, a magnetic storage device, or any of the above suitable combination.
  • the present invention can also be implemented in the form of a program product, which includes program codes, when the program product runs on a terminal device, the program code is used to cause the terminal device to execute the implementation The steps of the camera occlusion detection method of Embodiment 1.
  • the program code for executing the present invention can be written in any combination of one or more programming languages, and the program code can be completely executed on the user equipment, partially executed on the user equipment, as an independent
  • the software package executes on the user's device, partly on the user's device, partly on the remote device, or entirely on the remote device.

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Abstract

本发明公开了一种摄像头遮挡检测方法及系统、电子设备及存储介质。其中，摄像头遮挡检测方法包括以下步骤：响应于进入非单摄的拍摄模式，控制主摄像头和辅摄像头进行拍摄；其中，所述主摄像头和所述辅摄像头所拍摄的空间区域一致；获取所述主摄像头拍摄的第一图片以及所述辅摄像头拍摄的第二图片；根据所述第一图片和所述第二图片的相似度确定所述辅摄像头是否被遮挡。本发明无需额外增加硬件成本或者受限于特定的摄像头，也能实现判断辅摄像头是否被遮挡，具有更高的通用性和适配性。另外，根据主辅摄像头同时拍摄图片的相似度判断辅摄像头是否被遮挡，与通过用户主观判断相比，准确性较高。

Description

摄像头遮挡检测方法及系统、电子设备及存储介质
本申请要求申请日为2020年12月25日的中国专利申请CN202011563466.4的优先权。本申请引用上述中国专利申请的全文。
技术领域
本发明涉及电子设备技术领域，特别涉及一种摄像头遮挡检测方法及系统、电子设备及存储介质。
背景技术
随着移动技术的发展，移动终端已经成为人们日常生活中常用的电子产品。随着人们对移动终端的依赖程度越来越高，对其性能要求也就越来越高，尤其是移动终端的拍照性能。而具有单摄像头的移动终端的拍照性能在一定程度上已经达到极限，想要在拍照性能上有所突破，势必要借助多个摄像头。
目前，市面上有双摄手机和三摄手机，甚至有的手机厂商还推出了四摄手机和五摄手机。利用多个摄像头可以实现背景虚化、重对焦、夜景/暗光拍照增强、光学变焦、HDR以及三维应用等复杂的功能，为了实现上述功能，不同手机厂商的解决方案也不同。有的手机厂商提供的解决方案属于“真多摄”方案，也即利用多个摄像头同时成像的结果进行算法处理，以实现上述功能。但是有的手机厂商提供的解决方案属于“假多摄”方案，也即虽然硬件上存在多个摄像头，但是在实现上述功能时仅利用单个摄像头成像的结果。当用户使用多摄功能时，无法分辨使用的手机是“真多摄”还是“假多摄”，如果是“真多摄”，用户无意中遮挡辅摄像头则会导致拍摄质量不佳，这时如果没有提示用户遮挡辅摄像头的话，会降低用户的拍照体验。
针对上述问题，现有技术中有以下几种判断多摄手机中辅摄像头是否被遮挡的方法：
第一、在多摄场景下通过查看拍照效果判断辅摄像头是否被遮挡。这种方法依赖于用户的主观判断，判断的准确度较低。
第二、通过环境光的亮度判断辅摄像头是否被遮挡。这种方法需要借助于环境光亮度实现，而统计环境光亮度信息需要经过aem统计模块，但是只有raw sensor才有aem统计模块，其它sensor例如yuv sensor并没有aem统计模块，因此也就获取不到环境光的亮度信息，如果使用这些sensor用作手机摄像头的话，则无法实现上述判断功能。
第三、在手机后板上安装距离传感器或者超声传感器，通过传感器检测物体到摄像头的距离，从而判断辅摄像头是否被遮挡。这种方法需要额外安装传感器，导致手机的成本增加。
发明内容
本发明要解决的技术问题是为了克服现有技术中的上述缺陷，提供一种摄像头遮挡检测方法及系统、电子设备及存储介质。
本发明是通过下述技术方案来解决上述技术问题：
本发明的第一方面提供一种摄像头遮挡检测方法，包括以下步骤：
响应于进入非单摄的拍摄模式，控制所述主摄像头和所述辅摄像头进行拍摄；其中，所述主摄像头和所述辅摄像头所拍摄的空间区域一致；
获取所述主摄像头拍摄的第一图片以及所述辅摄像头拍摄的第二图片；
根据所述第一图片和所述第二图片的相似度确定所述辅摄像头是否被遮挡。
可选地，所述获取所述主摄像头拍摄的第一图片以及所述辅摄像头拍摄的第二图片，具体包括：
分别对所述主摄像头和所述辅摄像头拍摄的图片进行预处理，得到视场角和尺寸均相同的第一图片和第二图片。
可选地，所述根据所述第一图片和所述第二图片的相似度确定所述辅摄 像头是否被遮挡，具体包括：
计算所述第一图片和所述第二图片的相似度；
判断所述相似度是否低于预设值；
若是，则确定所述辅摄像头被遮挡；
若否，则确定所述辅摄像头未被遮挡。
可选地，所述计算所述第一图片和所述第二图片的相似度，具体包括：
将所述第一图片裁剪为若干第一子图片，以及将所述第二图片裁剪为若干第二子图片；其中，所述第一子图片和所述第二子图片的尺寸和数量均相同；
针对每个第一子图片，分别判断所述第一子图片与对应位置的第二子图片是否相似；
根据判断的所有相似结果计算所述第一图片和所述第二图片的相似度。
本发明的第二方面提供一种摄像头遮挡检测系统，包括：
控制模块，用于响应于进入非单摄的拍摄模式，控制所述主摄像头和所述辅摄像头进行拍摄；其中，所述主摄像头和所述辅摄像头所拍摄的空间区域一致；
获取模块，用于获取所述主摄像头拍摄的第一图片以及所述辅摄像头拍摄的第二图片；
确定模块，用于根据所述第一图片和所述第二图片的相似度确定所述辅摄像头是否被遮挡。
可选地，所述获取模块具体用于分别对所述主摄像头和所述辅摄像头拍摄的图片进行预处理，得到视场角和尺寸均相同的第一图片和第二图片。
可选地，所述确定模块具体包括：
计算单元，用于计算所述第一图片和所述第二图片的相似度；
确定单元，用于判断所述相似度是否低于预设值，并在是的情况下确定所述辅摄像头被遮挡；以及在否的情况下确定所述辅摄像头未被遮挡。
可选地，所述计算单元具体包括：
裁剪子单元，用于将所述第一图片裁剪为若干第一子图片，以及将所述第二图片裁剪为若干第二子图片；其中，所述第一子图片和所述第二子图片的尺寸和数量均相同；
判断子单元，用于针对每个第一子图片，分别判断所述第一子图片与对应位置的第二子图片是否相似；
计算子单元，用于根据判断的所有相似结果计算所述第一图片和所述第二图片的相似度。
本发明的第三方面提供一种电子设备，包括存储器、处理器以及存储在存储器上并可在处理器上运行的计算机程序，所述处理器执行所述计算机程序时实现如第一方面所述的摄像头遮挡检测方法。
本发明的第四方面提供一种计算机可读存储介质，其上存储有计算机程序，所述计算机程序被处理器执行时实现如第一方面所述的摄像头遮挡检测方法。
本发明的积极进步效果在于：在进入非单摄的拍摄模式后，控制主摄像头和辅摄像头同时进行拍摄，并根据主摄像头拍摄的第一图片以及辅摄像头拍摄的第二图片的相似度确定所述辅摄像头是否被遮挡。与现有技术相比，本发明无需额外增加硬件成本或者受限于特定的摄像头，也能实现判断辅摄像头是否被遮挡，具有更高的通用性和适配性。另外，根据主辅摄像头同时拍摄图片的相似度判断辅摄像头是否被遮挡，与通过用户主观判断相比，准确性较高。
进一步地，通过将第一图片裁剪为多个第一子图片，以及将第二图片裁剪为多个第二子图片，分别比较子图片是否相似，再基于子图片的相似结果计算第一图片和第二图片的相似度，提高了相似度计算的准确性，进而提高了判断辅摄像头是否被遮挡的准确性，提升了用户体验。
附图说明
图1为本发明实施例1提供的一种摄像头遮挡检测方法的流程图。
图2为本发明实施例1提供的一种步骤S103的具体方法流程图。
图3为本发明实施例1提供的第一图片裁剪为第一子图片的效果图。
图4为本发明实施例1提供的第二图片裁剪为第二子图片的效果图。
图5为本发明实施例2提供的一种摄像头遮挡检测系统的结构框图。
图6为本发明实施例3提供的一种电子设备的结构示意图。
具体实施方式
下面通过实施例的方式进一步说明本发明，但并不因此将本发明限制在所述的实施例范围之中。
本发明实施例提供的摄像头遮挡检测方法可以应用于包括主摄像头和辅摄像头的电子设备。其中，主摄像头和辅摄像头所拍摄的空间区域一致。在一种可能的设计中，主摄像头和辅摄像头位于电子设备的同一侧，例如均为后置摄像头。辅摄像头的数量可以为一个，也可以为两个，甚至更多。
其中，主摄像头/辅摄像头用于捕获静态图像或视频。通常，摄像头可以包括感光元件比如镜头组和图像传感器，其中，镜头组包括多个透镜(凸透镜或凹透镜)，用于采集待拍摄物体反射的光信号，并将采集的光信号传递给图像传感器。图像传感器根据所述光信号生成待拍摄物体的原始图像。
需要说明的是，在电子设备的相机应用程序处于打开状态或者运行状态时，显示屏显示的预览画面即为主摄像头拍摄的画面。也就是说，如果主摄像头被遮挡的话，通过查看预览画面可以直接知晓，具体地，预览画面被遮挡说明主摄像头被遮挡，预览画面未被遮挡说明主摄像头未被遮挡。因此，本发明实施例提供的摄像头遮挡检测方法主要用于检测辅摄像头是否被遮挡。
实施例1
如图1所示，本实施例提供一种摄像头遮挡检测方法，包括以下步骤S101～S103：
步骤S101、响应于进入非单摄的拍摄模式，控制主摄像头和辅摄像头进行拍摄。其中，主摄像头和辅摄像头所拍摄的空间区域一致。
需要说明的是，非单摄的拍摄模式是指在非单摄场景下进行拍摄，具体地，在进入非单摄的拍摄模式之后，响应于触发的拍摄操作，利用至少两个摄像头同时拍摄以实现不同的拍摄功能，例如景深模式、光学变焦等。
在具体实施的一个例子中，响应于用户触发的拍摄操作，例如用户通过点击“拍摄”图标实现实时或延时拍摄。在具体实施的另一个例子中，响应于系统定时拍摄操作，例如进入非单摄的拍摄模式预设时长之后执行拍摄操作。
步骤S102、获取所述主摄像头拍摄的第一图片以及所述辅摄像头拍摄的第二图片。
在步骤S102可选的一种实施方式中，分别对所述主摄像头和所述辅摄像头拍摄的图片进行预处理，得到视场角和尺寸均相同的第一图片和第二图片。
由于主摄像头和辅摄像头在电子设备上的具体位置不同，例如主摄像头和辅摄像头横向布置，或者纵向布置，因此，主摄像头和辅摄像头的视场角不同。本实施方式对主摄像头和辅摄像头拍摄的图片进行预处理，以使得两张图片的视场角和尺寸保持相同。
在预处理具体实施的一个例子中，先通过裁剪两张图片的边缘，再对裁剪的图片进行单应性矩阵映射，以得到视场角和尺寸均相同的第一图片和第二图片。具体地，上述裁剪图片的比例与主辅摄像头的布置方式相关。
为了提高图片的处理效率，在步骤S102可选的一种实施方式中，上述预处理还包括：将主摄像头和辅摄像头拍摄的图片均转为单通道的灰度图。
需要说明的是，第一个图片和第二图片的格式需相同，通常为YUV格 式或者RGB格式。在一个具体的例子中，主摄像输出图片的格式为raw格式，辅摄像头输出图片的格式为YUV格式，那么需要将主摄像输出的图片进行格式转换，即将raw格式转换为YUV格式。
在步骤S102可选的一种实施方式中，若仅能获取到主摄像头拍摄的第一图片，而无法获取到辅摄像头拍摄的第二图片，则说明所述电子设备在非单摄的拍摄模式下依然使用的是单个摄像头即主摄像头进行拍摄，并未实现真正的非单摄拍摄。在这种情况下，无需继续执行后续的步骤S103。
步骤S103、根据所述第一图片和所述第二图片的相似度确定所述辅摄像头是否被遮挡。
在可选的一种实施方式中，如图2所示，步骤S103具体包括以下步骤S103a～S103d：
步骤S103a、计算所述第一图片和所述第二图片的相似度。
在具体实施的一个例子，步骤S103a包括以下步骤S103a1S103a3：
步骤S103a1、将所述第一图片裁剪为若干第一子图片，以及将所述第二图片裁剪为若干第二子图片；其中，所述第一子图片和所述第二子图片的尺寸和数量均相同。其中，裁剪为子图片的数量越多，第一图片和第二图片的相似度计算地越准确。
步骤S103a2、针对每个第一子图片，分别判断所述第一子图片与对应位置的第二子图片是否相似。
在具体实施中，可以根据哈希算法判断第一子图片与对应位置的第二子图片是否相似，具体地，计算第一子图片的哈希值与第二子图片的哈希值之间的汉明距离，汉明距离越小，说明第一子图片和第二子图片越相似。
在一个具体的例子中，经过预处理之后，第一图片和第二图片的尺寸均为27*24，将第一图片裁剪为9幅尺寸为9*8的第一子图片，如图3所示。同样，将第二图片也裁剪为9幅尺寸为9*8的第二子图片，如图4所示。使用差异哈希算法判断第一子图片11和对应位置的第二子图片21是否相似， 若第一子图片11的哈希值与第二子图片21的哈希值之间的汉明距离小于10，则认为第一子图片11与第二子图片21相似，否则认为第一子图片11与第二子图片21不相似。
步骤S103a3、根据判断的所有相似结果计算所述第一图片和所述第二图片的相似度。
在上述例子中，如图3和4所示，根据第一子图片11与第二子图片21的相似结果、第一子图片12与第二子图片22的相似结果、第一子图片13与第二子图片23的相似结果、第一子图片14与第二子图片24的相似结果、第一子图片15与第二子图片25的相似结果、第一子图片16与第二子图片26的相似结果、第一子图片17与第二子图片27的相似结果、第一子图片18与第二子图片28的相似结果以及第一子图片19与第二子图片29的相似结果计算第一图片和第二图片的相似度。
在一个具体的例子中，设置默认相似度为1％，以及存在一组相似的第一子图片和第二子图片，则将第一图片和第二图片的相似度增加11％。若存在9组相似的第一子图片和第二子图片，则第一图片和第二图片的相似度则为100％。其中，默认相似度以及存在一组相似的第一子图片和第二子图片对应增加的相似度可以根据第一子图片和第二子图片的数量进行设置。
本实施方式中，通过将第一图片裁剪为多个第一子图片，以及将第二图片裁剪为多个第二子图片，分别比较子图片是否相似，再基于子图片的相似结果计算第一图片和第二图片的相似度，提高了相似度计算的准确性，进而提高了判断辅摄像头是否被遮挡的准确性，提升了用户体验。
步骤S103b、判断所述相似度是否低于预设值，若是，则执行步骤S103c，若否，则执行步骤S103d。其中，预设值可以根据实际情况进行设置，例如可以设置为90％，或者80％。
步骤S103c、确定所述辅摄像头被遮挡。在具体实施的一个例子中，在确定辅摄像头被遮挡的情况下，输出提示消息，以提示用户辅摄像头被遮挡。 用户接收到提示消息之后可以通过调整遮挡物例如人手，以使得辅摄像头不再继续被遮挡。
步骤S103d、确定所述辅摄像头未被遮挡。
本实施例中，进入非单摄的拍摄模式后，控制主摄像头和辅摄像头同时进行拍摄，并根据主摄像头拍摄的第一图片以及辅摄像头拍摄的第二图片的相似度确定所述辅摄像头是否被遮挡。与现有技术相比，本实施例无需额外增加硬件成本或者受限于特定的摄像头，也能实现判断辅摄像头是否被遮挡，具有更高的通用性和适配性。另外，根据主辅摄像头同时拍摄图片的相似度判断辅摄像头是否被遮挡，与通过用户主观判断相比，准确性较高。
实施例2
本实施例提供一种摄像头遮挡检测系统50，如图5所示，包括控制模块51、获取模块52以及确定模块53。
控制模块51用于响应于进入非单摄的拍摄模式，控制主摄像头和辅摄像头进行拍摄。其中，主摄像头和辅摄像头所拍摄的空间区域一致。
获取模块52用于获取所述主摄像头拍摄的第一图片以及所述辅摄像头拍摄的第二图片。
在可选的一种实施方式中，上述获取模块具体用于分别对所述主摄像头和所述辅摄像头拍摄的图片进行预处理，得到视场角和尺寸均相同的第一图片和第二图片。
确定模块53用于根据所述第一图片和所述第二图片的相似度确定所述辅摄像头是否被遮挡。
在可选的一种实施方式中，上述确定模块具体包括：
计算单元，用于计算所述第一图片和所述第二图片的相似度；
确定单元，用于判断所述相似度是否低于预设值，并在是的情况下确定所述辅摄像头被遮挡；以及在否的情况下确定所述辅摄像头未被遮挡。
在可选的一种实施方式中，上述计算单元具体包括：
裁剪子单元，用于将所述第一图片裁剪为若干第一子图片，以及将所述第二图片裁剪为若干第二子图片；其中，所述第一子图片和所述第二子图片的尺寸和数量均相同；
判断子单元，用于针对每个第一子图片，分别判断所述第一子图片与对应位置的第二子图片是否相似；
计算子单元，用于根据判断的所有相似结果计算所述第一图片和所述第二图片的相似度。
需要说明的是，上述摄像头遮挡检测系统具体可以是单独的芯片、芯片模组或者终端，也可以是集成于终端内的芯片或者芯片模组。
关于上述实施例中描述的摄像头遮挡检测系统包含的各个模块/单元，其可以是软件模块/单元，也可以是硬件模块/单元，或者也可以部分是软件模块/单元，部分是硬件模块/单元。例如，对于应用于或集成于芯片的各个装置、产品，其包含的各个模块/单元可以都采用电路等硬件的方式实现，或者，至少部分模块/单元可以采用软件程序的方式实现，该软件程序运行于芯片内部集成的处理器，剩余的部分模块/单元可以采用电路等硬件方式实现；对于应用于或集成于芯片模组的各个装置、产品，其包含的各个模块/单元可以都采用电路等硬件的方式实现，不同的模块/单元可以位于芯片模组的同一组件(例如芯片、电路模块等)或者不同组件中，或者，至少部分模块/单元可以采用软件程序的方式实现，该软件程序运行于芯片模组内部集成的处理器，剩余的部分模块/单元可以采用电路等硬件方式实现；对于应用于或集成于终端的各个装置、产品，其包含的各个模块/单元可以都采用电路等硬件的方式实现，不同的模块/单元可以位于终端内同一组件(例如，芯片、电路模块等)或者不同组件中，或者，至少部分模块/单元可以采用软件程序的方式实现，该软件程序运行于终端内部集成的处理器，剩余的部分模块/单元可以采用电路等硬件方式实现。
实施例3
图6为本实施例提供的一种电子设备的结构示意图。所述电子设备包括存储器、处理器及存储在存储器上并可在处理器上运行的计算机程序，所述处理器执行所述程序时实现实施例1的摄像头遮挡检测方法。图6显示的电子设备3仅仅是一个示例，不应对本发明实施例的功能和使用范围带来任何限制。
本发明实施例中的电子设备可以为手机、平板电脑、PDA(Personal Digital Assistant，个人数字助理)、POS(Point of Sales，销售终端)、车载终端、穿戴设备等，其中，穿戴设备可以为智能手环、智能手表、腕带、智能眼镜、项链等。
电子设备3的组件可以包括但不限于：上述至少一个处理器4、上述至少一个存储器5、连接不同系统组件(包括存储器5和处理器4)的总线6。
总线6包括数据总线、地址总线和控制总线。
存储器5可以包括易失性存储器，例如随机存取存储器(RAM)51和/或高速缓存存储器52，还可以进一步包括只读存储器(ROM)53。
存储器5还可以包括具有一组(至少一个)程序模块54的程序/实用工具55，这样的程序模块54包括但不限于：操作系统、一个或者多个应用程序、其它程序模块以及程序数据，这些示例中的每一个或某种组合中可能包括网络环境的实现。
处理器4通过运行存储在存储器5中的计算机程序，从而执行各种功能应用以及数据处理，例如本发明实施例1的摄像头遮挡检测方法。
电子设备3也可以与一个或多个外部设备7(例如键盘、指向设备等)通信。这种通信可以通过输入/输出(I/O)接口8进行。并且，电子设备3还可以通过网络适配器9与一个或者多个网络(例如局域网(LAN)，广域网(WAN)和/或公共网络，例如因特网)通信。如图6所示，网络适配器9通过总线6与电子设备3的其它模块通信。应当明白，尽管图6中未示出，可以结合电子设备3使用其它硬件和/或软件模块，包括但不限于：微代码、设 备驱动器、冗余处理器、外部磁盘驱动阵列、RAID(磁盘阵列)系统、磁带驱动器以及数据备份存储系统等。
应当注意，尽管在上文详细描述中提及了电子设备的若干单元/模块或子单元/模块，但是这种划分仅仅是示例性的并非强制性的。实际上，根据本发明的实施方式，上文描述的两个或更多单元/模块的特征和功能可以在一个单元/模块中具体化。反之，上文描述的一个单元/模块的特征和功能可以进一步划分为由多个单元/模块来具体化。
实施例4
本实施例提供了一种计算机可读存储介质，其上存储有计算机程序，所述程序被处理器执行时实现实施例1的摄像头遮挡检测方法的步骤。
其中，可读存储介质可以采用的更具体可以包括但不限于：便携式盘、硬盘、随机存取存储器、只读存储器、可擦拭可编程只读存储器、光存储器件、磁存储器件或上述的任意合适的组合。
在可能的实施方式中，本发明还可以实现为一种程序产品的形式，其包括程序代码，当所述程序产品在终端设备上运行时，所述程序代码用于使所述终端设备执行实现实施例1的摄像头遮挡检测方法的步骤。
其中，可以以一种或多种程序设计语言的任意组合来编写用于执行本发明的程序代码，所述程序代码可以完全地在用户设备上执行、部分地在用户设备上执行、作为一个独立的软件包执行、部分在用户设备上部分在远程设备上执行或完全在远程设备上执行。
虽然以上描述了本发明的具体实施方式，但是本领域的技术人员应当理解，这仅是举例说明，本发明的保护范围是由所附权利要求书限定的。本领域的技术人员在不背离本发明的原理和实质的前提下，可以对这些实施方式做出多种变更或修改，但这些变更和修改均落入本发明的保护范围。

Claims (10)

  1. 一种摄像头遮挡检测方法，其特征在于，包括以下步骤：
    响应于进入非单摄的拍摄模式，控制主摄像头和辅摄像头进行拍摄；其中，所述主摄像头和所述辅摄像头所拍摄的空间区域一致；
    获取所述主摄像头拍摄的第一图片以及所述辅摄像头拍摄的第二图片；
    根据所述第一图片和所述第二图片的相似度确定所述辅摄像头是否被遮挡。
  2. 如权利要求1所述的摄像头遮挡检测方法，其特征在于，所述获取所述主摄像头拍摄的第一图片以及所述辅摄像头拍摄的第二图片，具体包括：
    分别对所述主摄像头和所述辅摄像头拍摄的图片进行预处理，得到视场角和尺寸均相同的第一图片和第二图片。
  3. 如权利要求1或2所述的摄像头遮挡检测方法，其特征在于，所述根据所述第一图片和所述第二图片的相似度确定所述辅摄像头是否被遮挡，具体包括：
    计算所述第一图片和所述第二图片的相似度；
    判断所述相似度是否低于预设值；
    若是，则确定所述辅摄像头被遮挡；
    若否，则确定所述辅摄像头未被遮挡。
  4. 如权利要求3所述的摄像头遮挡检测方法，其特征在于，所述计算所述第一图片和所述第二图片的相似度，具体包括：
    将所述第一图片裁剪为若干第一子图片，以及将所述第二图片裁剪为若干第二子图片；其中，所述第一子图片和所述第二子图片的尺寸和数量均相同；
    针对每个第一子图片，分别判断所述第一子图片与对应位置的第二子图片是否相似；
    根据判断的所有相似结果计算所述第一图片和所述第二图片的相似度。
  5. 一种摄像头遮挡检测系统，其特征在于，包括：
    控制模块，用于响应于进入非单摄的拍摄模式，控制主摄像头和辅摄像头进行拍摄；其中，所述主摄像头和所述辅摄像头所拍摄的空间区域一致；
    获取模块，用于获取所述主摄像头拍摄的第一图片以及所述辅摄像头拍摄的第二图片；
    确定模块，用于根据所述第一图片和所述第二图片的相似度确定所述辅摄像头是否被遮挡。
  6. 如权利要求5所述的摄像头遮挡检测系统，其特征在于，所述获取模块具体用于分别对所述主摄像头和所述辅摄像头拍摄的图片进行预处理，得到视场角和尺寸均相同的第一图片和第二图片。
  7. 如权利要求5或6所述的摄像头遮挡检测系统，其特征在于，所述确定模块具体包括：
    计算单元，用于计算所述第一图片和所述第二图片的相似度；
    确定单元，用于判断所述相似度是否低于预设值，并在是的情况下确定所述辅摄像头被遮挡；以及在否的情况下确定所述辅摄像头未被遮挡。
  8. 如权利要求7所述的摄像头遮挡检测系统，其特征在于，所述计算单元具体包括：
    裁剪子单元，用于将所述第一图片裁剪为若干第一子图片，以及将所述第二图片裁剪为若干第二子图片；其中，所述第一子图片和所述第二子图片的尺寸和数量均相同；
    判断子单元，用于针对每个第一子图片，分别判断所述第一子图片与对应位置的第二子图片是否相似；
    计算子单元，用于根据判断的所有相似结果计算所述第一图片和所述第二图片的相似度。
  9. 一种电子设备，包括存储器、处理器以及存储在存储器上并可在处理 器上运行的计算机程序，其特征在于，所述处理器执行所述计算机程序时实现权利要求1-4中任一项所述的摄像头遮挡检测方法。
  10. 一种计算机可读存储介质，其上存储有计算机程序，其特征在于，所述计算机程序被处理器执行时实现如权利要求1-4中任一项所述的摄像头遮挡检测方法。
PCT/CN2021/131283 2020-12-25 2021-11-17 摄像头遮挡检测方法及系统、电子设备及存储介质 WO2022134957A1 (zh)

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