Exposure control device, imaging device, exposure control method, and program

Abstract

The invention provides an exposure control device, an imaging device, an exposure control method, and a program capable of suppressing inappropriate variation in brightness of a setting region set in an image. An exposure control device according to the present invention performs: a process for acquiring an image signal output from an imaging element; acquiring a specific subject region in an image represented by the image signal; calculating a first exposure value of a setting region set in the image and a second exposure value of a subject region; determining a first weight with respect to the first exposure value and a second weight with respect to the second exposure value on the basis of a first determination for determining the degree of importance of the subject region with respect to the set region and a second determination for determining the positional relationship between the set region and the subject region; and calculating a third exposure value by weighting and adding the first exposure value and the second exposure value using the first weight and the second weight.

Description

Technical Field

[0001] The technology of the present invention relates to an exposure control device, an imaging device, an exposure control method, and a program. Background Art

[0002] Patent document 1 discloses an aperture control device, characterized in that it includes a face detection mechanism, which, in an aperture control device that adjusts the aperture opening based on an output signal of an imaging element that performs photoelectric conversion on incident light passing through the aperture, detects a face from a photographic image based on the output signal of the imaging element, and adjusts the aperture opening based on at least one of the position of the face contained in the photographic image on the photographic image, the size on the photographic image, and the direction.

[0003] Patent document 2 discloses an information processing device, characterized in that it comprises: an image acquisition mechanism for acquiring an image obtained by photographing a subject using a camera unit; a detection method setting mechanism for setting a detection method for the subject with respect to the image; a subject detection mechanism for detecting the subject based on a detection method determined by the detection method setting mechanism; and an exposure determination mechanism for determining exposure based on a detection result obtained from the subject detection mechanism, wherein the detection method setting mechanism is capable of setting different detection methods for each different area in the image based on specified information when photographing the image to obtain the image.

[0004] Patent Document 1: Japanese Patent Application Publication No. 2008-233470

[0005] Patent Document 2: Japanese Patent Application Publication No. 2020-072469 Summary of the invention

[0006] The technical object of the present invention is to provide an exposure control device, an imaging device, an exposure control method, and a program that can suppress inappropriate changes in brightness of a set area set in an image.

[0007] In order to achieve the above-mentioned purpose, the exposure control device of the present invention includes a processor and a memory, and the processor performs the following processing: acquiring an image signal output from an imaging element; acquiring a specific subject area in the image represented by the image signal; calculating a first exposure value of a set area set in the image and a second exposure value of the subject area; determining a first weight relative to the first exposure value and a second weight relative to the second exposure value based on a first judgment of determining the importance of the subject area relative to the set area and a second judgment of determining the positional relationship between the set area and the subject area; and calculating a third exposure value by weighted addition of the first exposure value and the second exposure value using the first weight and the second weight.

[0008] Preferably, when the processor determines in the second determination that the subject region is within the set region, the processor determines the first weight and the second weight independently of the positional relationship.

[0009] Preferably, when the processor determines in the second determination that the subject region is outside the set region, the processor determines the first weight and the second weight based on the positional relationship.

[0010] Preferably, the processor determines the weighting coefficient based on a result of the first determination, and determines the correction coefficient based on a result of the second determination.

[0011] Preferably, when the first exposure value is set to E1, the second exposure value is set to E2, the third exposure value is set to E3, the first weight is set to W1, the second weight is set to W2, the weight coefficient is set to α, and the correction coefficient is set to β, the processor performs the following processing: the first weight and the second weight are determined in a manner to satisfy W1=1-α×β and W2=α×β, and the third exposure value is calculated according to E3=E1×W1+E2×W2.

[0012] Preferably, the processor determines the correction coefficient to 1 when it is determined in the second determination that the subject region is within the set region.

[0013] Preferably, when the processor determines in the second determination that the subject region is outside the set region, the processor determines the correction coefficient based on the positional relationship.

[0014] Preferably, the positional relationship includes a distance between the setting area and the subject area.

[0015] Preferably, the larger the distance, the smaller the correction coefficient.

[0016] Preferably, the first determination is a determination based on a ratio of a size of the subject region to a size of a set region.

[0017] Preferably, the processor determines the first weight and the second weight independently of the positional relationship when the ratio of the size of the subject area to the size of the set area is smaller than the first threshold and the absolute value of the difference between the first exposure value and the second exposure value is smaller than the second threshold.

[0018] When the ratio of the size of the subject area to the size of the set area is less than the first threshold, the absolute value of the difference between the first exposure value and the second exposure value is less than the second threshold, and the subject contained in the subject area is a specific subject, the processor can determine the first weight and the second weight without relying on the positional relationship.

[0019] Preferably, the subject region is a face region of a person.

[0020] Preferably, the processor uses a machine learning model to obtain the subject area.

[0021] Preferably, the set area is an image display area for displaying an image within the set area, an image recording area for recording an image within the set area, or an image cropping area for electronic zoom or image stabilization.

[0022] An imaging device according to the present invention includes the above-mentioned exposure control device and an imaging element.

[0023] The exposure control method of the present invention includes the following processing steps performed by a processor: acquiring an image signal output from an imaging element; acquiring a specific subject area within the image represented by the image signal; calculating a first exposure value of a set area set within the image and a second exposure value of the subject area; determining a first weight relative to the first exposure value and a second weight relative to the second exposure value based on a first determination of the importance of the subject area relative to the set area and a second determination of the positional relationship between the set area and the subject area; and calculating a third exposure value by weighted addition of the first exposure value and the second exposure value using the first weight and the second weight.

[0024] The program of the present invention includes the following steps: acquiring an image signal output from an imaging element; acquiring a specific subject area within the image represented by the image signal; calculating a first exposure value of a set area set in the image and a second exposure value of the subject area; determining a first weight relative to the first exposure value and a second weight relative to the second exposure value based on a first determination of the importance of the subject area relative to the set area and a second determination of the positional relationship between the set area and the subject area; and calculating a third exposure value by weighted addition of the first exposure value and the second exposure value using the first weight and the second weight. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 This is a diagram showing an example of the internal structure of the imaging device.

[0026] Figure 2 This is a block diagram showing an example of the functional structure of a processor.

[0027] Figure 3 This is a diagram showing an example of a setting area.

[0028] Figure 4 : is a figure which shows an example of the object area acquisition process.

[0029] Figure 5 It is a diagram showing a configuration example of an exposure value calculation unit.

[0030] Figure 6 This is a diagram conceptually showing the exposure value calculation process.

[0031] Figure 7This is a diagram showing an example when the subject area is outside the set area.

[0032] Figure 8 This is a diagram showing an example when the subject area is within the set area.

[0033] Fig. 9 This is a diagram showing an example of the relationship between the weight coefficient and the ratio.

[0034] Fig.10 This is a diagram showing an example of the relationship between the correction coefficient and the ratio.

[0035] Fig.11 This is a flowchart showing the flow of the overall processing executed by the imaging device.

[0036] Fig.12 This is a flowchart showing an example of the flow of exposure value calculation processing.

[0037] Fig.13 It is a diagram showing the configuration of an exposure value calculation unit according to the first modification.

[0038] Fig.14 This is a flowchart showing the flow of exposure value calculation processing according to the first modification example.

[0039] Fig.15 This is a flowchart showing the flow of exposure value calculation processing according to the second modification.

[0040] Fig.16 It is a diagram showing the subject region acquisition processing involved in the third modification example.

[0041] Fig.17 This is a diagram showing an example of setting an area as an image cropping area for electronic zoom.

[0042] Fig.18 This is a diagram showing an example of setting an area as an image cutout area for image stabilization. DETAILED DESCRIPTION

[0043] An example of an embodiment according to the technology of the present invention will be described with reference to the drawings.

[0044] First, the terms used in the following description are explained.

[0045] In the following description, "IC" is the abbreviation of "Integrated Circuit". "CPU" is the abbreviation of "Central Processing Unit". "ROM" is the abbreviation of "Read Only Memory". "RAM" is the abbreviation of "Random Access Memory". "CMOS" is the abbreviation of "Complementary Metal Oxide Semiconductor".

[0046] “FPGA” is the abbreviation of “Field Programmable Gate Array”. “PLD” is the abbreviation of “Programmable Logic Device”. “ASIC” is the abbreviation of “Application Specific Integrated Circuit”. “OVF” is the abbreviation of “Optical View Finder”. “EVF” is the abbreviation of “Electronic View Finder”. “CNN” is the abbreviation of “Convolutional Neural Network”.

[0047] As one embodiment of the imaging device, a lens-interchangeable digital camera is taken as an example to explain the technology of the present invention. In addition, the technology of the present invention is not limited to the lens-interchangeable type, and can also be applied to a lens-integrated digital camera.

[0048] Figure 1 An example of the structure of the imaging device 10 is shown. The imaging device 10 is a lens-interchangeable digital camera. The imaging device 10 is composed of a main body 11 and an imaging lens 12 that is replaceably mounted on the main body 11. The imaging lens 12 is mounted on the front surface side of the main body 11 via a camera-side mount 11A and a lens-side mount 12A.

[0049] The main body 11 is provided with an operating device 13 including a dial, a release button, a touch panel, etc., and receiving user operations. The operation modes of the imaging device 10 include, for example, a still image shooting mode, a moving image shooting mode, and an image display mode. The operating device 13 is operated by the user when setting the operation mode. In addition, the operating device 13 is operated by the user when starting still image shooting or moving image shooting.

[0050] In addition, a viewfinder 14 is provided on the main body 11. Here, the viewfinder 14 is a hybrid viewfinder (registered trademark). The so-called hybrid viewfinder refers to a viewfinder that selectively uses an optical viewfinder (hereinafter referred to as "OVF") and an electronic viewfinder (hereinafter referred to as "EVF"), for example. The user can observe an optical image or a live view image of the subject projected by the viewfinder 14 through a viewfinder eyepiece portion (not shown).

[0051] Furthermore, a display 15 is provided on the back side of the main body 11. An image based on an image signal obtained by shooting and various menu screens are displayed on the display 15. The user can also observe a live view image displayed on the display 15 instead of the viewfinder 14.

[0052] The main body 11 and the imaging lens 12 are electrically connected by contact between an electrical contact 11B provided on the camera-side mount 11A and an electrical contact 12B provided on the lens-side mount 12A.

[0053] The imaging lens 12 includes a zoom lens 30, a focus lens 31, an aperture 32, and a driver 33. The zoom lens 30, the focus lens 31, and the aperture 32 are arranged in this order from the subject side along the optical axis A. The zoom lens 30 and the focus lens 31 can move in the direction of the optical axis A. The zoom lens 30, the focus lens 31, and the aperture 32 constitute an imaging optical system. The type, number, and arrangement order of the lenses constituting the imaging optical system are not limited to Figure 1 Example shown.

[0054] Furthermore, the imaging lens 12 includes a driver 33. The driver 33 is composed of, for example, a CPU, a RAM, and a ROM. The lens drive control unit 34 is electrically connected to the processor 40 in the main body 11 via the electrical contact 12B and the electrical contact 11B.

[0055] The driver 33 drives the zoom lens 30, the focus lens 31, and the aperture 32 according to the control signal sent from the processor 40. The driver 33 drives the zoom lens 30 to control the zoom ratio according to the zoom ratio control signal sent from the processor 40. In addition, the driver 33 drives the focus lens 31 according to the focus control signal sent from the processor 40 to adjust the focus position of the imaging lens 12.

[0056] The aperture 32 has an opening with a variable opening diameter centered on the optical axis A. The driver 33 drives the aperture 32 based on an aperture adjustment control signal sent from the processor 40 to adjust the amount of incident light on the light receiving surface 20A of the imaging sensor 20. The value representing the opening diameter (i.e., the opening degree) of the aperture 32 is referred to as an "aperture value."

[0057] Furthermore, the main body 11 includes an imaging sensor 20, a processor 40, and a memory 42. The processor 40 controls the operations of the imaging sensor 20, the memory 42, the operating device 13, the viewfinder 14, and the display 15.

[0058] The processor 40 is composed of, for example, a CPU. In this case, the processor 40 executes various processes based on the program 43 stored in the memory 42. In addition, the processor 40 may be composed of a collection of multiple IC chips. In addition, the processor 40 and the memory 42 constitute the "exposure control device" involved in the technology of the present invention.

[0059] The imaging sensor 20 is, for example, a CMOS image sensor. In the imaging sensor 20, the optical axis A is orthogonal to the light receiving surface 20A, and the optical axis A is arranged to be located at the center of the light receiving surface 20A. Light passing through the imaging lens 12 is incident on the light receiving surface 20A. A plurality of pixels that generate signals by photoelectric conversion are formed on the light receiving surface 20A. The imaging sensor 20 generates an image signal D and outputs it by photoelectrically converting the light incident on each pixel. In addition, the imaging sensor 20 is an example of an "imaging element" involved in the technology of the present invention.

[0060] Furthermore, a color filter array of a Bayer arrangement is arranged on the light receiving surface of the image sensor 20, and any one of the color filters of R (red), G (green), and B (blue) is arranged opposite to each pixel. In addition, some of the plurality of pixels arranged on the light receiving surface of the image sensor 20 may be phase difference detection pixels for detecting a phase difference involved in focus control.

[0061] Furthermore, the imaging sensor 20 has an electronic shutter function and can electronically change the shutter speed. The shutter speed is controlled by the processor 40 .

[0062] Figure 2 An example of the functional structure of the processor 40 is shown. For example, the processor 40 executes processing by the program 43 stored in the memory 42, thereby realizing various functional units. Figure 2 As shown, for example, the processor 40 implements a main control unit 50 , an imaging control unit 51 , an image acquisition unit 52 , a display control unit 53 , a region determination unit 54 , a subject region acquisition unit 55 , and an exposure value calculation unit 56 .

[0063] The main control unit 50 controls the overall operation of the imaging device 10 based on output information from the operating device 13. The imaging control unit 51 controls the imaging sensor 20 to execute imaging processing for causing the imaging sensor 20 to perform imaging operations. The imaging control unit 51 drives the imaging sensor 20 in a still image capturing mode or a moving image capturing mode.

[0064] The imaging sensor 20 outputs an image signal D obtained by imaging. For example, the image signal D is a signal for one frame. The imaging sensor 20 outputs the image signal D for each frame period.

[0065] The image acquisition unit 52 acquires the image signal D output from the imaging sensor 20 and outputs the acquired image signal D to the display control unit 53, the subject region acquisition unit 55, the exposure value calculation unit 56, etc. The image acquisition unit 52 performs image processing such as demosaicing on the acquired image signal D and then outputs the result.

[0066] The region determination unit 54 determines the setting region RG based on the output information from the operating device 13, and sets the setting region RG in the image represented by the image signal D. In the present embodiment, the setting region RG is an image display region for displaying the image in the setting region RG on the display 15 or the viewfinder 14. Of the images represented by the image signal D, only the image in the setting region RG is displayed on the display 15. The size or shape of the setting region RG is specified by the user operating the operating device 13. In addition, the region determination unit 54 may set the size or shape of the setting region RG based on the size of the recorded image specified by operating the operating device 13. The region determination unit 54 supplies information indicating the setting region RG to the display control unit 53 and the exposure value calculation unit 56.

[0067] The display control unit 53 causes the display 15 to display the image within the set area RG based on the image signal D and the set area RG. In addition, the display control unit 53 causes the display 15 to display a live view image based on the image signal D periodically input from the image acquisition unit 52 during the shooting preparation operation before still image shooting or moving image shooting.

[0068] The subject area acquisition unit 55 acquires a subject area RO including a subject to be acquired from the entirety of the image represented by the image signal D. The user can use the operating device 13 to specify a subject (a person's face, a bird, an airplane, a car, etc.) as the acquisition object. In addition, a plurality of subjects can also be designated as the acquisition object. The subject area acquisition unit 55 supplies information representing the subject area RO to the exposure value calculation unit 56. In addition, the entirety of the image represented by the image signal D refers to the entirety of the image represented by the signal output from the effective area where light is incident on the imaging sensor 20, and the signal output from the optical dark area, etc. is excluded. The subject area RO including the subject to be acquired is an example of a "specific subject area" involved in the technology of the present invention. A specific subject area refers to an area including a subject arbitrarily selected by design or by the user.

[0069] The exposure value calculation unit 56 performs exposure value calculation processing based on the image signal D and the information indicating the setting area RG and the object area RO. The details will be described later, but the exposure value calculation unit 56 calculates the first exposure value E1 of the setting area RG and the second exposure value E2 of the object area RO, and performs weighted addition of the first exposure value E1 and the second exposure value E2, thereby calculating the third exposure value E3 as the final exposure value. The exposure value calculation unit 56 outputs the calculated third exposure value E3 to the main control unit 50. In addition, the exposure value is a value determined according to the amount of light incident on the light receiving surface 20A of the imaging sensor 20 during the exposure period, and is controlled by the aperture value (F value) and the shutter speed (exposure time). The exposure value is also called an EV value. The first exposure value E1 represents the brightness of the setting area RG. The second exposure value E2 represents the brightness of the object area RO.

[0070] The main control unit 50 performs exposure control to control the aperture diameter of the diaphragm 32 and the shutter speed of the imaging sensor 20 according to the third exposure value E3. When performing exposure control, the main control unit 50 uses a program map to determine a combination of an aperture value and a shutter speed that can obtain the third exposure value E3.

[0071] In addition, Figure 2 Although not shown in the figure, the processor 40 has a function of calculating the defocus amount based on the signal output from the phase difference detection pixel of the imaging sensor 20. The main control unit 50 controls the focus lens 31 based on the calculated defocus amount to adjust the focus position.

[0072] Figure 3 An example of setting region RG is shown. The image represented by the image signal D is rectangular. For example, the setting region RG is rectangular, and its center of gravity O coincides with the center of gravity of the image represented by the image signal D. The aspect ratio of the setting region RG may also be the same as the aspect ratio of the image represented by the image signal D. In this embodiment, the setting region RG is a display region, and the size or aspect ratio is changed according to the size of the recorded image, etc.

[0073] Figure 4 1 shows an example of the subject region acquisition processing by the subject region acquisition unit 55. In the present embodiment, the subject region acquisition unit 55 uses a well-known template matching method to acquire the subject region RO including the subject to be acquired. Specifically, the subject region acquisition unit 55 uses a rectangular template image corresponding to the subject to be acquired to perform a search, and acquires the region with the highest matching degree with the template image from the entire image represented by the image signal D as the subject region RO. Figure 4 This shows a case where the subject region RO is a face region of a person. In the present embodiment, the subject region RO is represented by a rectangular frame.

[0074] Figure 5 A configuration example of the exposure value calculation unit 56 is shown. Figure 6 The following conceptually shows the exposure value calculation process performed by the exposure value calculation section 56. The exposure value calculation section 56 includes a first exposure value calculation section 61, a second exposure value calculation section 62, a first determination section 63, a second determination section 64, a weight determination section 65, and a weighted addition section 66.

[0075] The first exposure value calculation unit 61 measures light for a set area RG in the image represented by the image signal D, and calculates a first exposure value E1 based on the obtained light measurement value. The second exposure value calculation unit 62 measures light for a subject area RO in the image represented by the image signal D, and calculates a second exposure value E2 based on the obtained light measurement value. For example, the first exposure value calculation unit 61 and the second exposure value calculation unit 62 perform multi-segment light measurement.

[0076] The first determination unit 63 performs a first determination of the importance of the subject region RO relative to the set region RG. In the present embodiment, the importance is a ratio R1 of the size of the subject region RO relative to the size of the set region RG. More specifically, the ratio R1 is a ratio of the area of ​​the subject region RO to the area of ​​the set region RG. The larger the ratio R1, the higher the importance.

[0077] The second determination unit 64 performs a second determination of the positional relationship between the setting area RG and the subject area RO. In the present embodiment, the second determination unit 64 determines whether the subject area RO is within the setting area RG. For example, the second determination unit 64 finds the center of gravity P of the subject area RO and determines whether the center of gravity P is within the setting area RG. Hereinafter, "the subject area RO is within the setting area RG" means "the center of gravity P of the subject area RO is within the setting area RG", and "the subject area RO is outside the setting area RG" means "the center of gravity P of the subject area RO is outside the setting area RG".

[0078] When the subject region RO is outside the setting region RG, the second determination unit 64 calculates a ratio R2 of the distance from the center of gravity O of the setting region RG to the center of gravity P of the subject region RO to the distance from the outer periphery of the setting region RG to the center of gravity P of the subject region RO.

[0079] Figure 7 This shows an example when the subject region RO is outside the set region RG. Figure 7 In the formula ( ), B represents the intersection point where the straight line connecting the centroid O and the centroid P intersects the outer periphery of the set region RG. In this case, the second determination unit 64 calculates the ratio R2 of the distance from the centroid O to the intersection point B to the distance from the centroid O to the centroid P. When the subject region RO is outside the set region RG, R2<1.

[0080] Figure 8 This shows an example when the subject region RO is within the set region RG. Figure 8 In the equation ( ), B represents the intersection point where the extension line formed by extending the straight line connecting the center of gravity O and the center of gravity P intersects the outer periphery of the set region RG. In this case, the second determination unit 64 calculates the ratio R2 of the distance from the center of gravity O to the intersection point B to the distance from the center of gravity O to the center of gravity P. When the subject region RO is located within the set region RG, R2≥1.

[0081] The weight determination unit 65 determines the first weight W1 for the first exposure value E1 and the second weight W2 for the second exposure value E2 based on the result of the first determination by the first determination unit 63 and the result of the second determination by the second determination unit 64. Specifically, the weight determination unit 65 determines the weight coefficient α based on the result of the first determination and determines the correction coefficient β based on the result of the second determination, and then determines the first weight W1 and the second weight W2 in a manner that satisfies the following equations (1) and (2).

[0082] W1=1-α×β……(1)

[0083] W2=α×β……(2)

[0084] Here, the weight coefficient α is a coefficient indicating the importance of the subject region RO relative to the set region RG obtained by the first determination. The correction coefficient β is a coefficient indicating the positional relationship between the set region RG obtained by the second determination and the subject region RO. In the present embodiment, the weight coefficient α is a coefficient dependent on the above-mentioned ratio R1. The correction coefficient β is a coefficient dependent on the above-mentioned ratio R2.

[0085] Fig. 9 1 shows an example of the relationship between the weight coefficient α and the ratio R1. The relationship between the weight coefficient α and the ratio R1 is predetermined and stored in the memory 42 as data, for example. Fig. 9 In the relationship shown, when R1 ≥ 1, α = 1, and when R1 < 1, the weight coefficient α decreases as the ratio R1 decreases.

[0086] The weight determination unit 65 determines the weight coefficient α based on the data indicating the relationship between the ratio R1 obtained by the first determination by the first determination unit 63 and the weight coefficient α and the ratio R1. When the size of the subject region RO is equal to or larger than the size of the setting region RG, the weight coefficient α becomes a fixed value (in Fig. 9 In the example shown, it is "1"). On the other hand, when the size of the subject region RO is smaller than the size of the setting region RG, the smaller the size of the subject region RO, the smaller the weight coefficient α. That is, the weight coefficient α increases monotonically as the ratio R1 increases.

[0087] In addition, within the range of 0≤R1<1, the relationship between the weight coefficient α and the ratio R1 may be linear. Also, within the range of 0≤R1<1, the relationship between the weight coefficient α and the ratio R1 may be nonlinear.

[0088] Fig.10 2 shows an example of the relationship between the correction coefficient β and the ratio R2. The relationship between the correction coefficient β and the ratio R2 is predetermined and stored in the memory 42 as data, for example. Fig.10 In the relationship shown, when R2 ≥ 1, β = 1, and when R2 < 1, the correction coefficient β becomes smaller as the ratio R2 becomes smaller.

[0089] The weight determination unit 65 determines the correction coefficient β based on the ratio R2 obtained by the second determination by the second determination unit 64 and the data indicating the relationship between the correction coefficient β and the ratio R2. When the subject region RO is within the set region RG, the correction coefficient β becomes a fixed value (in Fig.10 On the other hand, when the subject region RO is outside the set region RG, the larger the distance between the subject region RO and the set region RG (for example, the distance between the center of gravity O and the center of gravity P), the smaller the correction coefficient β. That is, the correction coefficient β increases monotonically as the ratio R2 increases.

[0090] In addition, in the range of 0≤R2<1, the relationship between the correction coefficient β and the ratio R2 may be linear. Also, in the range of 0≤R2<1, the relationship between the correction coefficient β and the ratio R2 may be nonlinear. Also, in the range of 0≤R2<1, the correction coefficient β may be set to a fixed value (e.g., "0").

[0091] Thus, when it is determined in the second determination that the subject region RO is within the setting region RG, the weight determination unit 65 determines the correction coefficient β to be 1. That is, when it is determined in the second determination that the subject region RO is within the setting region RG, the weight determination unit 65 determines the first weight W1 and the second weight W2 regardless of the positional relationship between the setting region RG and the subject region RO.

[0092] On the other hand, when the weight determination unit 65 determines in the second determination that the subject region RO is outside the setting region RG, the correction coefficient β is determined based on the positional relationship between the setting region RG and the subject region RO. That is, when the weight determination unit 65 determines in the second determination that the subject region RO is outside the setting region RG, the first weight W1 and the second weight W2 are determined based on the positional relationship between the setting region RG and the subject region RO.

[0093] The weighted addition unit 66 performs weighted addition on the first exposure value E1 and the second exposure value E2 using the first weight W1 and the second weight W2, thereby calculating the third exposure value E3. Specifically, the weighted addition unit 66 calculates the third exposure value E3 using the relationship expressed by the following equation (3). Here, the relationship of 0≤W1≤1 and 0≤W2≤1 is satisfied.

[0094] E3=E1×W1+E2×W2……(3)

[0095] Fig.11 1 shows the flow of the overall processing executed by the imaging device 10 . Fig.11 An example of the processing flow in the moving image shooting mode is shown.

[0096] First, the main control unit 50 determines whether there is an imaging start command issued by the user operating the operating device 13 (step S10). If there is an imaging start command (step S10: Yes), the main control unit 50 controls the imaging control unit 51 to cause the imaging sensor 20 to perform imaging (step S11).

[0097] The image acquisition unit 52 acquires one frame of the image signal D output from the imaging sensor 20 (step S12). The region determination unit 54 determines the set region RG based on the output information from the operating device 13, and sets the set region RG in the image represented by the image signal D (step S13). The display control unit 53 causes the display 15 to display the image in the set region RG in the image represented by the image signal D (step S14).

[0098] The subject region acquisition unit 55 acquires the subject region RO including the subject to be acquired from the image represented by the image signal D (step S15). The exposure value calculation unit 56 performs exposure value calculation processing based on the image signal D and the information representing the setting region RG and the subject region RO (step S16). The main control unit 50 performs exposure control based on the third exposure value E3 calculated by the exposure value calculation processing (step S17).

[0099] Fig.12 An example of the flow of the exposure value calculation process is shown. First, as described above, the first exposure value calculation unit 61 calculates the first exposure value E1 (step S20). Next, the exposure value calculation unit 56 determines whether the subject region RO is acquired by the subject region acquisition unit 55 (step S21). When the subject region RO is not acquired (step S21: No), the exposure value calculation unit 56 uses the first exposure value E1 calculated in step S20 as the third exposure value E3 (step S22), and ends the exposure value calculation process.

[0100] On the other hand, when the subject region RO is acquired (step S21: Yes), as described above, the second exposure value calculation unit 62 calculates the second exposure value E2 (step S23). Next, the first determination unit 63 performs the first determination (step S24). As described above, the weight determination unit 65 determines the weight coefficient α based on the result of the first determination (step S25). For example, step S25 is performed by applying the ratio R1 obtained in the first determination to the relationship between the weight coefficient α and the ratio R1 (refer to Fig. 9 ) to carry out.

[0101] Next, the second determination unit 64 performs the above-mentioned second determination (step S26). The weight determination unit 65 determines whether the subject region RO is outside the set region RG based on the result of the second determination (step S27). When the subject region RO is outside the set region RG (step S27: Yes), as described above, the weight determination unit 65 determines the correction coefficient β based on the positional relationship between the set region RG and the subject region RO (step S28). On the other hand, when the subject region RO is within the set region RG (step S27: No), the weight determination unit 65 determines the correction coefficient β to be 1 (step S29). For example, steps S27 to S29 are performed by applying the ratio R2 obtained in the second determination to the relationship between the correction coefficient β and the ratio R2 (refer to Fig.10 ) to carry out.

[0102] After step S28 or step S29, the weight determination unit 65 determines the first weight W1 and the second weight W2 based on the determined weight coefficient α and correction coefficient β and the above equations (1) and (2) (step S30). Then, the weighted addition unit 66 calculates the third exposure value E3 based on the determined first weight W1 and second weight W2 and the above equation (3) (step S31). Thus, the exposure value calculation process ends.

[0103] As described above, the technology of the present invention is characterized in that, based on the first judgment and the second judgment, the first weight W1 of the setting area RG relative to the first exposure value E1 and the second weight W2 of the subject area RO relative to the second exposure value E2 are determined, and the first exposure value E1 and the second exposure value E2 are weightedly added using the first weight W1 and the second weight W2 to calculate the third exposure value E3, wherein the first judgment determines the importance of the subject area RO relative to the setting area RG, and the second judgment determines the positional relationship between the setting area RG and the subject area RO.

[0104] In the prior art, when calculating the third exposure value E3 as the final exposure value, the positional relationship between the setting area RG and the subject area RO is not considered, so the third exposure value E3 does not depend on whether the subject area RO is in the setting area RG. Therefore, even if the subject area RO does not exist in the setting area RG, the third exposure value E3 will be affected by the second exposure value E2 of the subject area RO. For example, when displaying an image of the setting area RG, even if the subject area RO such as a person does not exist in the setting area RG and the scene in the setting area RG does not change, such as Figure 7 As shown, when the subject region RO exists outside the set region RG, the brightness of the displayed image may change due to the influence of the subject region RO. That is, in the prior art, due to the subject region RO existing outside the set region RG, the brightness of the set region RG may change inappropriately.

[0105] According to the technique of the present invention, since the third exposure value E3 is calculated in consideration of the positional relationship between the setting region RG and the subject region RO, it is possible to suppress inappropriate changes in the brightness of the setting region RG.

[0106] Various modifications of the above-described embodiment will be described below.

[0107] [First Modification]

[0108] In the above embodiment, the weight determination unit 65 determines the first weight W1 and the second weight W2 based on the first and second determination results. However, the first and second weights W1 and W2 may be determined in consideration of the first and second exposure values ​​E1 and E2.

[0109] Fig.13 FIG. 5 shows the structure of the exposure value calculation unit 56 according to the first modification. Fig.13 As shown, in this modification, the weight determination unit 65 determines the first weight W1 and the second weight W2 using the first exposure value E1 and the second exposure value E2 in addition to the first determination result and the second determination result. The other structures of the exposure value calculation unit 56 involved in this modification are the same as those in the above-mentioned embodiment.

[0110] Fig.14 FIG. 4 is a flow chart of the exposure value calculation process according to the first modification. Fig.12 The exposure value calculation process according to the above-described embodiment is different in that steps S40 and S41 are added between step S25 and step S26 .

[0111] After determining the weight coefficient α in step S25, the weight determination unit 65 determines whether the ratio R1 obtained in the first determination is less than the first threshold value (step S40). The ratio R1 being less than the first threshold value indicates that the size of the subject region RO is small relative to the size of the set region RG, and the importance of the subject region RO is low. That is, in step S40, it is determined whether the importance of the subject region RO is less than a specified value.

[0112] If the ratio R1 is not less than the first threshold value (step S40: No), the weight determination unit 65 shifts the process to step S26. That is, if the importance of the subject region RO is high, the same process as the above embodiment is performed.

[0113] On the other hand, when the ratio R1 is smaller than the first threshold value (step S40: Yes), the weight determination unit 65 determines whether the absolute value of the difference between the first exposure value E1 and the second exposure value E2 is smaller than the second threshold value (step S41). The absolute value being smaller than the second threshold value indicates that the brightness difference between the object region RO and its background is small. That is, in step S41, it is determined whether the brightness difference between the object region RO and its background is smaller than a predetermined value.

[0114] If the absolute value is not less than the second threshold value (step S41: No), the weight determination unit 65 transfers the process to step S26. That is, even if the importance of the subject region RO is low, when the brightness difference between it and the background is large, the same process as the above embodiment is performed.

[0115] On the other hand, when the absolute value is smaller than the second threshold value (step S41: Yes), the weight determination unit 65 transfers the process to step S29 to determine the correction coefficient β to 1. That is, when the importance of the subject region RO is low and the brightness difference between it and its background is small, the correction coefficient β is determined to be 1 regardless of the positional relationship between the setting region RG and the subject region RO, and the first weight W1 and the second weight W2 are determined.

[0116] As described above, in this variant example, the weight determination unit 65 determines the first weight W1 and the second weight W2 independently of the positional relationship between the set area RG and the subject area RO when the ratio R1 of the size of the subject area RO to the size of the set area RG is smaller than the first threshold and the absolute value of the difference between the first exposure value E1 and the second exposure value E2 is smaller than the second threshold.

[0117] When the importance of the subject region RO is low and the brightness difference between it and the background is small, the third exposure value E3 is not easily affected by the second exposure value E2 of the subject region RO. However, in this case, if the correction coefficient β is determined based on the positional relationship between the setting region RG and the subject region RO, the third exposure value E3 will change according to the change of the positional relationship, and unnecessary flickering may occur in the brightness of the setting region RG. In this modified example, when the importance of the subject region RO is low and the brightness difference between it and the background is small, the first weight W1 and the second weight W2 are determined without depending on the positional relationship, so that unnecessary flickering of the brightness of the setting region RG can be suppressed.

[0118] [Second Modification]

[0119] In the first variant, the weight determination unit 65 uses the first exposure value E1 and the second exposure value E2 in addition to the results of the first judgment and the second judgment to determine the first weight W1 and the second weight W2, but the first weight W1 and the second weight W2 may be determined by further considering the information of the subject contained in the subject area RO.

[0120] The configuration of the exposure value calculation unit 56 according to the present modification is the same as that of the first modification, except that the weight determination unit 65 acquires information of the subject included in the subject region RO from the subject region acquisition unit 55 .

[0121] Fig.15 FIG. 2 shows a flow of the exposure value calculation process according to the second modification. Fig.14 The exposure value calculation process according to the first modified example shown is different in that step S42 is added between step S41 and step S29 .

[0122] When the absolute value of the difference between the first exposure value E1 and the second exposure value E2 is less than the second threshold value (step S41: yes), the weight determination unit 65 determines whether the subject included in the subject area RO is a specific subject (step S42). The type of the specific subject is pre-stored as data in the memory 42. For example, the specific subject is a fast-moving object such as a drone or a bird. The specific subject is a subject that can move quickly within the image represented by the image signal D. In addition, it can also be configured so that the user can set the type of the specific subject using the operating device 13. The specific subject refers to a subject that is designed or arbitrarily selected by the user.

[0123] If the subject included in the subject region RO is not a specific subject (step S42: No), the process is transferred to step S26. That is, even if the importance of the subject region RO is low and the brightness difference between it and the background is small, when the subject included in the subject region RO is not a specific subject, the same process as the above embodiment is performed.

[0124] On the other hand, when the subject included in the subject region RO is a specific subject (step S42: Yes), the process is transferred to step S29 to determine the correction coefficient β to be 1. That is, when the importance of the subject region RO is low and the brightness difference between it and the background is small, and the subject included in the subject region RO is a specific subject, the correction coefficient β is determined to be 1 based on the positional relationship between the setting region RG and the subject region RO, and the first weight W1 and the second weight W2 are determined.

[0125] As described above, in this variation, the weight determination unit 65 determines the first weight W1 and the second weight W2 without depending on the positional relationship between the set area RG and the subject area RO when the ratio R1 of the size of the subject area RO to the size of the set area RG is smaller than the first threshold value, the absolute value of the difference between the first exposure value E1 and the second exposure value E2 is smaller than the second threshold value, and the subject included in the subject area RO is a specific subject.

[0126] When the subject included in the subject region RO is a fast-moving specific subject, since the positional relationship between the setting region RG and the subject region RO is easily changed, unnecessary flickering may occur in the brightness of the setting region RG. In this modified example, when the subject included in the subject region RO is a specific subject, the first weight W1 and the second weight W2 are determined independently of the influence of the positional relationship between the setting region RG and the subject region RO, thereby being able to suppress unnecessary flickering in the brightness of the setting region RG.

[0127] [Third Modification]

[0128] In the above-mentioned embodiment, the subject region acquisition unit 55 acquires the subject region RO by using the template matching method, but the subject region RO may be acquired by using a machine learning model.

[0129] Fig.16 4 shows the subject region acquisition process involved in the third modification example. Fig.16As shown, the machine learning completion model LM is composed of a neural network with an input layer, an intermediate layer and an output layer. The intermediate layer is composed of a plurality of neurons. The number of intermediate layers and the number of neurons in each intermediate layer can be appropriately changed. For example, the learning completion model LM is a CNN. The machine learning completion model LM performs machine learning using a plurality of images that pre-contain a specific subject area as teacher data.

[0130] The subject region acquisition unit 55 inputs the image signal D to the machine learning model LM. The machine learning model LM determines and outputs the subject region RO from the image represented by the image signal D. For example, the machine learning model LM outputs the result of segmentation for each pixel as a heat map. For example, when the acquisition object is a person's face, a set of pixels belonging to the person's face is determined as the subject region RO.

[0131] In this way, by using the machine learning model to obtain the object region RO, the object region RO can be obtained with high accuracy, so that the positional relationship between the setting region RG and the object region RO can be determined more accurately in the first determination described above. As a result, inappropriate changes in the brightness of the setting region RG can be suppressed with higher accuracy.

[0132] [Other Modifications]

[0133] In the above embodiment, the setting area RG is set as an image display area for displaying the image in the setting area RG, but the setting area RG may also be an image recording area for the image in the setting area RG. In this case, the image in the setting area RG is recorded as dynamic image data in a storage device such as the memory 42.

[0134] Furthermore, the setting area RG may also be an image cropping area for electronic zooming. Fig.17 As shown, the size of the setting area RG changes according to the zoom factor of the electronic zoom. Specifically, the larger the zoom factor of the electronic zoom, the smaller the setting area RG.

[0135] Furthermore, the setting area RG may also be an image cropping area for hand shake correction. Fig.17 As shown, the setting area RG changes its position in accordance with an output signal from an angular velocity sensor (not shown) such as a gyro sensor provided in the imaging device 10 so as to eliminate hand shake.

[0136] Furthermore, in the above-mentioned embodiment, the first determination unit 63 determines the ratio R1 of the size of the subject region RO to the size of the setting region RG as the importance of the subject region RO relative to the setting region RG, but the importance is not limited to the ratio R1. For example, the importance may also be the type of the subject. In this case, the weight determination unit 65 increases the weight coefficient α for the type of subject with higher importance.

[0137] Furthermore, in the above-mentioned embodiment, the positional relationship between the setting region RG and the subject region RO is determined based on the centroid P of the subject region RO, but the basis for determining the positional relationship is not limited to the centroid P of the subject region RO. For example, the subject region RO may be determined to be outside the setting region RG when at least a portion of the subject region RO is outside the setting region RG, and may be determined to be inside the setting region RG when all portions of the subject region RO are inside the setting region RG. Conversely, the subject region RO may be determined to be inside the setting region RG when at least a portion of the subject region RO is inside the setting region RG, and may be determined to be outside the setting region RG when all portions of the subject region RO are outside the setting region RG.

[0138] Furthermore, in the above-mentioned embodiment, the camera device 10 is set as a digital camera, but the camera device 10 may also be a monitoring camera. In this case, the display 15 may also be a monitor of a personal computer connected to the outside of the monitoring camera. Furthermore, the operating device 13 may also be a keyboard, a mouse, etc. of a personal computer connected to the outside of the monitoring camera.

[0139] Furthermore, the technology of the present invention can also be applied to electronic devices such as smartphones and tablet terminals with camera functions.

[0140] In the above-mentioned embodiment, as the hardware structure of the control unit, the processor 40 is used as an example, and various processors shown below can be used. Among the above-mentioned various processors, in addition to the CPU which is a common processor that functions by executing software (program), there are also processors such as FPGA whose circuit structure can be changed after manufacturing. FPGA includes a dedicated circuit, which is a processor having a circuit structure specially designed to execute specific processing such as PLD or ASIC.

[0141] The control unit may be composed of one of these various processors, or may be composed of a combination of two or more processors of the same type or different types (for example, a combination of multiple FPGAs or a combination of a CPU and an FPGA). Furthermore, multiple control units may be composed of one processor.

[0142] There are multiple examples of multiple control units composed of one processor. In the first example, as represented by computers such as clients and servers, there is a method in which one processor is composed of a combination of one or more CPUs and software, and the processor functions as multiple control units. In the second example, as represented by a system on chip (System On Chip: SOC), a processor that implements the functions of the entire system including multiple control units by one IC chip is used. In this way, the control unit can use one or more of the above-mentioned various processors to form a hardware structure.

[0143] Furthermore, as the hardware configuration of these various processors, more specifically, a circuit combining circuit elements such as semiconductor elements can be used.

[0144] Also, the program may be stored in a storage medium that is non-temporarily readable by a computer.

[0145] The recorded contents and illustrated contents shown above are detailed descriptions of the parts involved in the technology of the present invention, and are only an example of the technology of the present invention. For example, the description of the above-mentioned structure, function, action and effect is a description of an example of the structure, function, action and effect of the parts involved in the technology of the present invention. Therefore, without departing from the scope of the main purpose of the technology of the present invention, it is of course possible to delete unnecessary parts of the recorded contents and illustrated contents shown above, or add new elements, or replace them. In addition, in order to avoid complexity and facilitate understanding of the parts involved in the technology of the present invention, in the recorded contents and illustrated contents shown above, descriptions related to technical common sense that does not need to be specifically explained are omitted on the basis of being able to implement the technology of the present invention.

[0146] All documents, patent applications, and technical specifications described in this specification are incorporated herein by reference in the same manner as if each document, patent application, and technical specification was specifically and individually described as being incorporated by reference.

[0147] Through the above description, the following techniques can be mastered.

[0148] [Additional item 1]

[0149] An exposure control device includes a processor and a memory, wherein the processor performs the following processing:

[0150] acquiring an image signal output from an imaging element;

[0151] Acquire a specific subject area within the image represented by the image signal;

[0152] calculating a first exposure value of a set area set in the image and a second exposure value of the subject area;

[0153] determining a first weight with respect to the first exposure value and a second weight with respect to the second exposure value based on a first determination of determining the importance of the subject region with respect to the set region and a second determination of determining a positional relationship between the set region and the subject region; and

[0154] A third exposure value is calculated by weighted addition of the first exposure value and the second exposure value using the first weight and the second weight.

[0155] [Supplementary Item 2]

[0156] The exposure control device according to Supplementary Item 1, wherein:

[0157] When the processor determines in the second determination that the subject region is within the set region, the processor determines the first weight and the second weight independently of the positional relationship.

[0158] [Supplementary item 3]

[0159] The exposure control device according to Supplementary item 1 or 2, wherein:

[0160] When the processor determines in the second determination that the subject region is outside the set region, the processor determines the first weight and the second weight based on the positional relationship.

[0161] [Supplementary Item 4]

[0162] An exposure control device according to any one of Supplementary Items 1 to 3, wherein:

[0163] The processor performs the following processing:

[0164] Determining a weight coefficient according to the result of the first determination;

[0165] The correction coefficient is determined based on the result of the second determination.

[0166] [Supplementary Note 5]

[0167] The exposure control device according to Supplementary Item 4, wherein:

[0168] When the first exposure value is set to E1, the second exposure value is set to E2, the third exposure value is set to E3, the first weight is set to W1, the second weight is set to W2, the weight coefficient is set to α, and the correction coefficient is set to β,

[0169] The processor performs the following processing:

[0170] The first weight and the second weight are determined to satisfy W1=1-α×β and W2=α×β,

[0171] The third exposure value is calculated according to E3=E1×W1+E2×W2.

[0172] [Supplementary Item 6]

[0173] The exposure control device according to Supplementary item 4 or 5, wherein:

[0174] The processor determines the correction coefficient to 1 when it is determined in the second determination that the subject region is within the set region.

[0175] [Supplementary Note 7]

[0176] An exposure control device according to any one of Supplementary Items 4 to 6, wherein:

[0177] When the processor determines in the second determination that the subject region is outside the set region, the processor determines the correction coefficient based on the positional relationship.

[0178] [Supplementary Item 8]

[0179] An exposure control device according to any one of Supplementary Items 4 to 7, wherein:

[0180] The positional relationship includes a distance between the set area and the object area.

[0181] [Supplementary Item 9]

[0182] The exposure control device according to Supplementary Item 8, wherein:

[0183] The larger the distance, the smaller the correction coefficient.

[0184] [Supplementary Item 10]

[0185] An exposure control device according to any one of Supplementary Items 1 to 9, wherein:

[0186] The first determination is a determination based on a ratio of the size of the subject region to the size of the set region.

[0187] [Supplementary Note 11]

[0188] The exposure control device according to supplementary item 10, wherein:

[0189] The processor determines the first weight and the second weight independently of the positional relationship when the ratio of the size of the subject area to the size of the set area is smaller than a first threshold and the absolute value of the difference between the first exposure value and the second exposure value is smaller than a second threshold.

[0190] [Supplementary Item 12]

[0191] The exposure control device according to supplementary item 10, wherein:

[0192] The processor determines the first weight and the second weight independently of the positional relationship when the ratio of the size of the subject area to the size of the set area is smaller than the first threshold, the absolute value of the difference between the first exposure value and the second exposure value is smaller than the second threshold, and the subject contained in the subject area is a specific subject.

[0193] [Supplementary Item 13]

[0194] An exposure control device according to any one of Supplementary Items 1 to 12, wherein:

[0195] The subject area is a face area of ​​a person.

[0196] [Supplementary Item 14]

[0197] An exposure control device according to any one of Supplementary Items 1 to 13, wherein:

[0198] The processor uses a machine learning model to obtain the subject area.

[0199] [Supplementary Item 15]

[0200] An exposure control device according to any one of Supplementary Items 1 to 14, wherein:

[0201] The set area is an image display area for displaying an image within the set area, an image recording area for recording an image within the set area, or an image cropping area for electronic zoom or hand shake correction.

[0202] [Supplementary Item 16]

[0203] An imaging device comprising the exposure control device according to any one of Supplementary Items 1 to 15 and the imaging element.

[0204] Explanation of symbols

[0205] 10-camera device, 11-main body, 11A-camera side mount, 11B-electrical contact, 12-imaging lens, 12A-lens side mount, 12B-electrical contact, 13-operating device, 14-viewfinder, 15-display, 20-camera sensor, 20A-light receiving surface, 30-zoom lens, 31-focus lens, 33-driver, 34-lens drive control unit, 40-processor, 42-memory, 43-program, 50-main control unit, 51-camera control unit, 52-image acquisition unit, 53-display control unit, 54-area determination unit, 55-subject area acquisition unit, 56-exposure value calculation unit, 61-first exposure value calculation unit, 62-second exposure value calculation unit, 63-first judgment unit, 64-second judgment unit, 65-weight determination unit, 66-weighted addition unit, A-optical axis, B-intersection, D-image signal, E1-first exposure value, E2-second exposure value, E3-third exposure value, LM-machine learning completion model, O, P-center of gravity, RG-set area, RO-subject area, W1-first weight, W2-second weight.

Claims

1. An exposure control device, comprising a processor and a memory, wherein the processor performs the following processing: acquiring an image signal output from an imaging element; Acquire a specific subject area within the image represented by the image signal; calculating a first exposure value of a set area set in the image and a second exposure value of the subject area; determining a first weight with respect to the first exposure value and a second weight with respect to the second exposure value based on a first determination of determining the importance of the subject region with respect to the set region and a second determination of determining a positional relationship between the set region and the subject region; and A third exposure value is calculated by weighted addition of the first exposure value and the second exposure value using the first weight and the second weight.

2. The exposure control device according to claim 1, wherein: When the processor determines in the second determination that the subject region is within the set region, the processor determines the first weight and the second weight independently of the positional relationship.

3. The exposure control device according to claim 2, wherein: When the processor determines in the second determination that the subject region is outside the set region, the processor determines the first weight and the second weight based on the positional relationship.

4. The exposure control device according to claim 1, wherein: The processor performs the following processing: Determining a weight coefficient according to the result of the first determination; The correction coefficient is determined based on the result of the second determination.

5. The exposure control device according to claim 4, wherein: When the first exposure value is set to E1, the second exposure value is set to E2, the third exposure value is set to E3, the first weight is set to W1, the second weight is set to W2, the weight coefficient is set to α, and the correction coefficient is set to β, The processor performs the following processing: The first weight and the second weight are determined in such a manner as to satisfy W1=1-α×β and W2=α×β, The third exposure value is calculated according to E3=E1×W1+E2×W2.

6. The exposure control device according to claim 5, wherein: The processor determines the correction coefficient to 1 when it is determined in the second determination that the subject region is within the set region.

7. The exposure control device according to claim 6, wherein: When the processor determines in the second determination that the subject region is outside the set region, the processor determines the correction coefficient based on the positional relationship.

8. The exposure control device according to claim 7, wherein: The positional relationship includes a distance between the set area and the object area.

9. The exposure control device according to claim 8, wherein: The larger the distance, the smaller the correction coefficient.

10. The exposure control device according to claim 1, wherein: The first determination is a determination based on a ratio of the size of the subject region to the size of the set region.

11. The exposure control device according to claim 10, wherein: The processor determines the first weight and the second weight independently of the positional relationship when the ratio of the size of the subject area to the size of the set area is smaller than a first threshold and the absolute value of the difference between the first exposure value and the second exposure value is smaller than a second threshold.

12. The exposure control device according to claim 10, wherein: The processor determines the first weight and the second weight independently of the positional relationship when the ratio of the size of the subject area to the size of the set area is smaller than the first threshold, the absolute value of the difference between the first exposure value and the second exposure value is smaller than the second threshold, and the subject contained in the subject area is a specific subject.

13. The exposure control device according to claim 1, wherein: The subject area is a face area of ​​a person.

14. The exposure control device according to claim 1, wherein: The processor uses a machine learning model to obtain the subject area.

15. The exposure control device according to claim 1, wherein: The set area is an image display area for displaying an image within the set area, an image recording area for recording an image within the set area, or an image cropping area for electronic zoom or hand shake correction.

16. A camera device comprising: The exposure control device according to any one of claims 1 to 15; and The imaging element.

17. An exposure control method, comprising the steps of: acquiring an image signal output from an imaging element; Acquire a specific subject area within the image represented by the image signal; calculating a first exposure value of a set area set in the image and a second exposure value of the subject area; determining a first weight with respect to the first exposure value and a second weight with respect to the second exposure value based on a first determination of determining the importance of the subject region with respect to the set region and a second determination of determining a positional relationship between the set region and the subject region; and A third exposure value is calculated by weighted addition of the first exposure value and the second exposure value using the first weight and the second weight.

18. A program causing a processor to execute a process comprising the following steps: acquiring an image signal output from an imaging element; Acquire a specific subject area within the image represented by the image signal; calculating a first exposure value of a set area set in the image and a second exposure value of the subject area; determining a first weight with respect to the first exposure value and a second weight with respect to the second exposure value based on a first determination of determining the importance of the subject region with respect to the set region and a second determination of determining a positional relationship between the set region and the subject region; and A third exposure value is calculated by weighted addition of the first exposure value and the second exposure value using the first weight and the second weight.

Images