Image capture device, image capture device control method, and program

Abstract

To solve a problem that power is unnecessarily wasted by EVF.SOLUTION: An imaging device includes first imaging means for imaging a subject, a second imaging means arranged in a direction facing the first imaging means, and an electronic viewfinder which is arranged in the same direction as the second imaging means, and displays an image captured by the first imaging means, and controls the display of the electronic viewfinder based on image data captured by the second imaging means.SELECTED DRAWING: Figure 4

Description

[Technical Field]

[0001] The present invention relates to an imaging device having an eyepiece. [Background technology]

[0002] Conventionally, imaging devices with electronic viewfinders (EVFs) have been known. In imaging devices equipped with such EVFs, a proximity sensor is provided to determine whether a user is looking through the EVF and detects the user's presence (eye contact detection). The proximity sensor is a sensor for detecting the presence of an object nearby, but it does not guarantee that the user is actually looking through the EVF. Therefore, when a user is wearing a camera strap around their neck or when the camera is in contact with their body, the sensor may mistakenly detect the user's presence as being near the eye. This causes the EVF to remain displayed, resulting in unnecessary power consumption. Patent Document 1 (JP-A-2005-102626) therefore discloses a configuration that employs a pressure sensor and switches between power-saving mode and normal mode based on the output of the pressure sensor. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2013-225785 Summary of the Invention [Problem to be solved by the invention]

[0004] However, in the conventional technology disclosed in the above-mentioned patent document, simply switching modes based on the output result of a specific sensor does not determine whether what is actually detected matches what is desired to be detected, which may result in detecting more than necessary and thus wasting power.

[0005] Therefore, an object of the present invention is to reduce unnecessary power consumption by the EVF. [Means for solving the problem]

[0006] In order to achieve the above object, an imaging device of the present invention comprises: an electronic viewfinder arranged in the same orientation as the second imaging means and displaying an image captured by the first imaging means; a detection means for detecting a face from image data captured by the second imaging means; a determination means for determining whether or not a user is attempting to look into the electronic viewfinder based on the image data captured by the second imaging means; and a control means, wherein the control means, if the detection means does not detect a face, controls the image captured by the first imaging means not to be displayed on the electronic viewfinder without making a determination by the determination means; if the detection means detects a face, the control means executes a determination by the determination means, and if the determination means does not determine that the user is attempting to look into the electronic viewfinder, controls the image captured by the first imaging means not to be displayed on the electronic viewfinder; and if the determination means determines that the user is attempting to look into the electronic viewfinder, controls the image captured by the first imaging means to be displayed on the electronic viewfinder. [Effects of the Invention]

[0007] According to the present invention, it is possible to reduce unnecessary power consumption by the EVF. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a block diagram showing a configuration of an imaging device according to a first embodiment of the present invention. [Figure 2] FIG. 2 is a diagram illustrating the function of the imaging device according to the first embodiment of the present invention. [Figure 3] 1 is a diagram showing the appearance of an imaging device according to a first embodiment of the present invention, the lens mount side, and the display unit side. [Figure 4] 4 is a flowchart showing the operation of the imaging device according to the first embodiment of the present invention. [Figure 5] 1 is a conceptual diagram of a structure using a learning model of an imaging device according to a first embodiment of the present invention. [Figure 6] FIG. 2 is a diagram for explaining the operation of the system according to the first embodiment of the present invention. [Figure 7] 4 is a flowchart of a learning phase of the imaging device according to the first embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0009] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings.

[0010] The embodiment described below is an example of a means for realizing the present invention, and may be appropriately modified or changed depending on the configuration of the device to which the present invention is applied and various conditions. Furthermore, each embodiment may be appropriately combined.

[0011] [First embodiment] <Internal configuration of digital camera 100> 1 is a block diagram showing the configuration of an interchangeable lens unit camera according to an embodiment of the present invention. In FIG. 1, the imaging device is made up of a digital camera body 100 and an imaging lens 200 that guides incident light to an imaging element 105.

[0012] First, the configuration of the camera body 100 will be described.

[0013] The shutter control unit 104 controls the shutter 103 in cooperation with the lens control unit 204 that controls the aperture 203 based on exposure information from the image processing unit 106 .

[0014] The image sensor 105 forms an optical image of a subject (not shown) via the lens 205, the aperture 203, the lens mounts 202 and 102, and the shutter 103, and converts the optical image into an electrical signal.

[0015] Image processing unit 106 performs predetermined arithmetic processing on the video signal input from image sensor 105, and based on the calculation results, performs image processing such as pixel interpolation, color conversion, and white balance processing, and outputs the result to display unit 111. Furthermore, if eye-contact is detected based on the image acquired by in-camera 130, image processing unit 106 outputs the image to digital viewfinder unit 112. Image processing unit 106 also has an image compression function such as JPEG. Display unit 111 is a display with a larger display area than digital viewfinder unit 112.

[0016] The recording medium 107 is a removable memory such as a semiconductor memory for recording or reading image data.

[0017] The communication unit 121 is connected wirelessly or via a wired cable and transmits and receives video signals and audio signals. The communication unit 121 can also be connected to a wireless LAN or the Internet. The communication unit 121 can transmit captured images (including through images) and images recorded in the recording circuit 107, and can also receive image data and various other information from external devices.

[0018] The operation unit 124 is an operation means for inputting various predetermined operation instructions to the system control unit 150. These operation means are configured by any one of switches, dials, touch panels, pointing by line of sight detection, voice recognition devices, etc., or a combination thereof.

[0019] The system timer 122 measures the time used for various controls and the time of the built-in clock.

[0020] A RAM is used as the system memory 123. Constants and variables for the operation of the system control unit 150, programs read from the memory 140, and the like are loaded into the system memory 123. The system memory 123 also has the function of storing image data acquired by the in-camera 130.

[0021] The power switch 125 can be used to switch between power-on and power-off modes of the imaging device 100 .

[0022] The shutter button 126 is an operation unit for issuing a shooting instruction.

[0023] The first shutter switch 127 is turned on and generates a first shutter switch signal SW1 when the shutter button 126 provided on the imaging device 100 is pressed halfway (a shooting preparation instruction) during operation. The first shutter switch signal SW1 starts operations such as autofocus processing, auto exposure processing, auto white balance processing, and flash pre-emission processing.

[0024] The second shutter switch 128 is turned on when the shutter button 126 is fully pressed (a photographing instruction) and generates a second shutter switch signal SW2.

[0025] In response to the second shutter switch signal SW2, the system control unit 150 starts a series of operations for the image capture process, from reading out the signal from the image sensor 105 to writing image data to the recording circuit 107.

[0026] The in-camera 130 is a camera disposed so as to capture an image in a direction opposite to the image sensor 105 .

[0027] The memory 140 is an electrically erasable and storable non-volatile memory. For example, a ROM is used. Constants, programs, etc. for the operation of the system control unit 150 are stored. The programs referred to here are programs for executing various flowcharts described later in this embodiment.

[0028] The system control unit 150 is a control unit that has at least one processor, and controls the overall operation of the imaging device 100 .

[0029] The power supply control unit 160 is composed of a battery detection circuit, protection circuit, DC-DC converter, LDO regulator, etc. It has the function of protecting the load circuit connected to the power supply circuit by cutting off the power supply when it detects whether a battery is installed, the battery type, the remaining battery charge, or an overcurrent. Based on instructions from the system control unit, it controls the power supply unit 170 and supplies the desired power supply voltage to each unit of the imaging device 100 for the desired period of time.

[0030] The power supply unit 170 is made up of a primary battery such as an alkaline battery or a lithium battery, a secondary battery such as an NiCd battery, an NiMH battery, or a Li battery, an AC adapter, or the like.

[0031] The lens mounts 102 and 202 are interfaces for connecting the imaging device 100 to the lens unit 200. The connectors 101 and 201 are connectors for electrically connecting the imaging device 100 to the lens unit 200, and are controlled by the system control unit 150.

[0032] The lens unit 200 is an interchangeable lens type lens unit, and can guide an optical image of a subject (not shown) from a lens 205 through an aperture 203, lens mounts 202 and 102, and a shutter 103, and form an image on an imaging element 105.

[0033] Next, the configuration of the lens unit 200 will be described.

[0034] The lens control unit 204 controls the entire lens unit 200. The lens control unit 204 also has a memory for storing operational constants, variables, programs, etc., and a non-volatile memory function for storing identification information such as a number unique to the lens unit 200, management information, functional information such as maximum aperture value, minimum aperture value, and focal length, and current and past setting values. The lens control unit 204 controls the focusing of the lens 205 in accordance with the focus state of the image measured by the image processing unit 106, and is capable of performing an AF operation by changing the imaging position of the subject image incident on the image sensor 105. The lens control unit 204 also has a function for controlling the aperture 203 and the zooming of the lens 205.

[0035] <Digital Camera 100 Functions> Next, the functions of the digital camera 100 will be described with reference to FIG.

[0036] Reference numeral 141 denotes an accumulation area of ​​the system memory 123, which is composed of a finite buffer or the like. Reference numeral 142 denotes a storage area of ​​the memory 140, which stores image data and a rule base corresponding thereto. This is referenced when the determination unit 153 performs signal pattern matching. Reference numeral 151 denotes a calculation unit of the system control unit 150, which outputs image data output from the in-camera 130 to a control unit 152 of the system control unit 150.

[0037] Reference numeral 152 denotes a control section of the system control section 150 , which controls the calculation section 151 to store image data output from the in-camera 130 in the storage area 141 of the system memory 123 .

[0038] Furthermore, if the determination unit 153 determines that the eye is being placed in the viewfinder, it controls and outputs the signal to the digital viewfinder unit 112. Reference numeral 153 denotes a determination unit in the system control unit 150, which performs pattern matching between the signals accumulated in the accumulation area 141 and the image data stored in the memory area 142. Furthermore, based on a rule base, the image data accumulated in the accumulation area 141 is classified as either the user looking into the EVF or not looking into the EVF.

[0039] If it is classified as looking into the EVF, a signal for transitioning to the EVF display mode is output to the power supply control unit 160 and the control unit 152.

[0040] The power supply control unit 160 and the control unit 152 transition to the EVF display mode based on the determination result from the determination unit 153.

[0041] The learning unit 154 receives the image data stored in the memory area 142 as input and performs learning using a flag indicating whether the corresponding user is looking into the EVF or not as training data. The trained model that has completed this learning becomes an inference model that receives the image data from the in-camera as input and outputs whether the user is looking into the EVF or not.

[0042] <Digital Camera 100 Appearance> Next, the location of the in-camera 130 will be described with reference to Fig. 3. Fig. 3 shows an example showing the lens mount side and display unit side of the imaging device 100. The in-camera 130 is placed on the same surface as the display unit side, in a location where it can acquire image data of the user.

[0043] <Operation of the digital camera 100> A flowchart showing the operation of digital camera 100 will be described below with reference to Fig. 4. This flowchart starts when power switch 125 is turned on. This flowchart is also implemented by system control unit 150 controlling each unit of digital camera 100. Unless otherwise specified, each step in the following flowchart is executed under the control of system control unit 150.

[0044] In S100, power is supplied to each unit of the imaging device 100, and the imaging device 100 is turned on.

[0045] In S101, the in-camera 130 is activated and image data is acquired.

[0046] In S102, the control unit 152 of the system control unit 150 detects a person by setting a threshold for the feature points of the person from the image data obtained in S101 and detecting a match of a predetermined number of feature points or more. If a person is detected, the process proceeds to S103. On the other hand, if a person is not detected, S102 is repeated again.

[0047] In S103 , the control unit 152 of the system control unit 150 starts storing image data from the in-camera 130 in the storage area 141 of the system memory 123 .

[0048] In S104, the control unit 152 of the system control unit 150 sets a threshold value for the feature points of a person's face in the image data and detects a person when the feature points match a predetermined number or more. If a person's face is detected here, the process proceeds to S105. On the other hand, if a person's face is not detected, the process proceeds to S106.

[0049] In S105 , the control unit 152 of the system control unit 150 continues to store the image data of the in-camera 130 in the storage area 141 of the system memory 123 .

[0050] In S106, the control unit 152 of the system control unit 150 uses the system timer 122 to determine whether a predetermined time has elapsed since the person was detected in S102. If it is determined that the predetermined time has elapsed, the process proceeds to S107. On the other hand, if it is determined that the predetermined time has not elapsed, S104 is repeated again.

[0051] In S107, the signals stored in the storage area 141 of the system memory 123 are erased.

[0052] In S108, the control unit 152 of the system control unit 150 determines whether the facial feature point match is equal to or greater than a predetermined value by setting a threshold range. If the match is equal to or greater than the threshold, the process proceeds to S109.

[0053] In S110, the control unit 152 of the system control unit 150 uses the system timer 122 to determine whether a predetermined time has elapsed since the facial feature points were detected in S108.

[0054] If it is determined that the predetermined time has elapsed, the process proceeds to S111. On the other hand, if it is determined that the predetermined time has not elapsed, S108 is repeated again.

[0055] In S109 , the control unit 152 of the system control unit 150 ends the accumulation of the image data from the in-camera 130 in the accumulation area 141 of the system memory 123 .

[0056] In S112, the determination unit 153 of the system control unit 150 acquires the signal stored in the storage area 141 of the system memory 123 as input data.

[0057] In S113, the determination unit 153 of the system control unit 150 acquires the signal stored in the storage area 142 of the memory 140 as model data.

[0058] In S114, the determination unit 153 of the system control unit 150 performs pattern matching between the input data and the model data, and classifies the input data into whether the user is looking through the EVF or not based on the rule base.

[0059] In S115, the determination unit 153 of the system control unit 150 determines whether the input data is being viewed through the EVF or not, based on the result of S114. If it is determined that the input data is being classified as being viewed through the EVF, the process proceeds to S116. On the other hand, if it is determined that the input data is not being classified as being the end of operation, the process proceeds to S118.

[0060] In S116, the signals stored in the storage area 141 of the system memory 123 are erased.

[0061] In S117, the power supply control unit 160 controls the power supply unit 170 and the digital viewfinder unit 112 in accordance with the instruction for the EVF display mode.

[0062] In S118, the signals stored in the storage area 141 of the system memory 123 are erased.

[0063] In S119, the display on the display unit 111 is maintained, and the process returns to S102.

[0064] <Learn about 100 digital cameras> Next, we will explain a technology that uses a learning model to determine whether a user is looking through the EVF when a person is detected and then appropriately displays the EVF. FIG. 5 is a conceptual diagram showing the input / output structure using the learning model of this embodiment. 301 is input data. In steps S103 to S109 of FIG. 4, image data from the in-camera 130 is collected by storing it in the storage area 141 of the system memory 123.

[0065] Reference numeral 302 denotes output data, which consists of two types: one where the user is looking into the EVF and one where the user is not looking into the EVF. A learning model is constructed using the difference in the combination of changes in image data from the in-camera 130 as feature points, and the input data is classified.

[0066] Reference numeral 303 denotes a learning model. Specific examples of machine learning algorithms include nearest neighbor algorithms, naive Bayes algorithms, decision trees, and support vector machines. Also included is deep learning, which uses a neural network to generate features and connection weighting coefficients for learning. Any of the above algorithms that can be used can be used as appropriate and applied to this embodiment.

[0067] Fig. 6 shows the operation of a system to which the present invention can be applied, using the structure of Fig. 5. By using a learning model, it is possible to classify whether or not the user is looking into the EVF, and it is possible to transition to EVF display mode only when the user is looking into the EVF.

[0068] Image data acquired by the in-camera 130 is transmitted to the calculation unit 151. The results calculated by the calculation unit 151 are transmitted to the control unit 152. When storage is started by the control unit 152, the image data is transmitted to the storage area 141. Image data that has finished being stored is transmitted to the determination unit 153 as input data. A learning model is requested from the memory area 142.

[0069] The learning model is sent from the memory area 142 to the determination unit 153. The determination unit 153 classifies the input data as a human face or something else based on the learning model. If the classification result of the determination unit 153 is a human face, it instructs the power supply control unit 160 and the control unit 152 to transition to EVF display mode. The power supply control unit 160 controls the power supply unit 170, and the control unit 152 controls the digital viewfinder display unit 112, thereby transitioning to EVF display mode.

[0070] The learning unit 154 may also include an error detection unit and an update unit. The error detection unit obtains an error between model data and output data output from the output layer of the neural network in response to input data input to the input layer. The error detection unit may use a loss function to calculate the error between the model data and output data from the neural network.

[0071] The update unit updates the connection weighting coefficients between the nodes of the neural network based on the error obtained by the error detection unit so as to reduce the error. This update unit updates the connection weighting coefficients using, for example, an error backpropagation method. The error backpropagation method is a technique for adjusting the connection weighting coefficients between the nodes of each neural network so as to reduce the error.

[0072] Below, with reference to Figure 7, we will explain the flowchart in which, after classifying whether or not the user is looking through the EVF, an error is detected based on whether or not the user has performed a specified shooting operation within a specified time, and if an error occurs, the learning model is updated by re-learning.

[0073] In S400, the determination unit 153 of the system control unit 150 acquires the signal stored in the storage area 141 of the system memory 123 as input data 301.

[0074] In S401 , the determination unit 153 of the system control unit 150 acquires the learning model 303 stored in the storage area 142 of the memory 140 .

[0075] In S402, the determination unit 153 of the system control unit 150 inputs the input data 301 to the learning model 303 and classifies whether or not the user is looking into the EVF.

[0076] In S403, the determination unit 153 of the system control unit 150 determines whether the output data of S402 indicates looking into the EVF. If it is determined that the data is classified as looking into the EVF, the process proceeds to S404. On the other hand, if it is determined that the data is not classified as looking into the EVF, the process proceeds to S406. In S406, the signals accumulated in the accumulation area 141 of the system memory 123 are erased.

[0077] In S404, the determination unit 153 of the system control unit 150 determines whether or not a user operation has been performed based on a signal from the operation unit 124. If it is determined that an operation has been performed, the process proceeds to S405. On the other hand, if it is determined that no operation has been performed, the process proceeds to S407.

[0078] In S405, the learning unit 154 of the system control unit 150 re-learns the input data 301 assuming that the user is looking through the EVF, and updates the learning model 303.

[0079] In S406, the signals stored in the storage area 141 of the system memory 123 are erased.

[0080] In S407, the determination unit 153 of the system control unit 150 uses the system timer 122 to determine whether a predetermined time has elapsed since it was determined in S403 that the state was classified as looking into the EVF. If it is determined that the predetermined time has elapsed, the process proceeds to S406. On the other hand, if it is determined that the predetermined time has not elapsed, S404 is repeated again.

[0081] In S406, the signals stored in the storage area 141 of the system memory 123 are erased.

[0082] As described above, by pattern-matching the image data of the in-camera 130 when the user looks into the EVF with the model data, it is possible to classify whether the user is looking into the EVF or not, and transition to EVF display mode only when the user is looking into the EVF.

[0083] Furthermore, by including the learning unit 154, it is possible to accommodate individual user habits that are not applicable to pattern matching, and classification accuracy improves with use, making it possible to transition to an EVF display mode without false detection.

[0084] In this embodiment, an image capture device has been described as an example, but the present invention is not limited to this. As long as it is an image capture device that can determine that someone is looking into the EVF, the present invention can be applied regardless of its form.

[0085] Although the preferred embodiments of the present invention have been described above, the present invention is not limited to these embodiments, and various modifications and changes are possible within the scope of the gist of the present invention.

[0086] (Other Examples) The present invention can also be realized by supplying a program that realizes one or more functions of the above-described embodiments to a system or device via a network or a storage medium, and having one or more processors in the computer of the system or device read and execute the program.The present invention can also be realized by a circuit (e.g., ASIC) that realizes one or more functions.

Claims

1. An imaging device, a first imaging means for imaging a subject; a second imaging means disposed in a direction opposite to the first imaging means; an electronic viewfinder that is disposed in the same orientation as the second imaging means and that displays an image captured by the first imaging means; a detection means for detecting a face from image data captured by the second imaging means; a determination means for determining whether or not a user is looking into the electronic viewfinder based on image data captured by the second imaging means; a control means; The control means when the detection means does not detect a face, the determination means does not make a determination, and the image captured by the first imaging means is not displayed on the electronic viewfinder; When a face is detected by the detection means, the determination means executes a determination; when it is determined by the determination means that the user is not looking into the electronic viewfinder, control is performed so that the image captured by the first imaging means is not displayed on the electronic viewfinder; When the determination means determines that the user is looking into the electronic viewfinder, control is performed so that the image captured by the first imaging means is displayed on the electronic viewfinder. An imaging device characterized by:

2. The imaging device according to claim 1 , wherein the determining means determines whether or not the user is looking through the electronic viewfinder using a trained model.

3. The imaging device according to claim 2, further comprising a re-learning means for re-learning the trained model using the image data used by the judgment means to determine that the user is attempting to look through the electronic viewfinder as input data and information indicating that the user is attempting to look through the electronic viewfinder as training data when a process for capturing an image and recording image data is executed by the first imaging means before a predetermined time has elapsed after the judgment means has determined that the user is attempting to look through the electronic viewfinder.

4. further comprising a display means having a display area larger than that of the electronic viewfinder; The control means when it is determined by the determination means that the user is not looking into the electronic viewfinder, control is performed so that an image captured by the first imaging means is displayed on the display means; When the determination means determines that the user is looking into the electronic viewfinder, control is performed so that the image captured by the first imaging means is not displayed on the display means.

2. The imaging device according to claim 1.

5. The imaging device described in Claim 1, characterized in that the control means controls the judgment means to make a judgment in accordance with whether the face detected by the detection means satisfies a predetermined condition.

6. the detection means detects facial feature points from image data captured by the second imaging means, the control means controls the determination means to make a determination in response to the feature points detected by the detection means satisfying the predetermined condition.

6. The imaging device according to claim 5.

7. A storage means for storing image data captured by said second image capturing means from the time a face is detected by said detection means until said predetermined condition is satisfied, the determining means determines whether or not the user is looking into the electronic viewfinder based on the image data captured by the second imaging means from when the face is detected by the detecting means until when the predetermined condition is satisfied, which is stored in the storing means.

7. The imaging device according to claim 6.

8. The detection means is capable of detecting a person, the storage means starts storing image data captured by the second imaging means in response to the detection of a person by the detection means.

8. The imaging device according to claim 7.

9. 9. The imaging device according to claim 8, wherein the storage means erases the stored image data if a predetermined time has passed since the detection means detected a person without the detection means detecting the face of the person.

10. The imaging device described in Claim 7, characterized in that the storage means erases the stored image data if a predetermined time has passed after the detection means detects a face without the predetermined conditions being met.

11. A control method for an imaging device having a first imaging means for imaging a subject, a second imaging means arranged in a direction opposite to the first imaging means, and an electronic viewfinder arranged in the same direction as the second imaging means and displaying an image captured by the first imaging means, comprising: a detection step of detecting a face from image data captured by the second imaging means; a determination step of determining whether or not a user is looking into the electronic viewfinder based on image data captured by the second imaging means; If no face is detected in the detecting step, the determination in the determining step is not performed, and control is performed so that the image captured by the first imaging means is not displayed on the electronic viewfinder; If a face is detected in the detecting step, the determination in the determining step is executed; If it is not determined in the determining step that the user is looking into the electronic viewfinder, control is performed so that the image captured by the first imaging means is not displayed on the electronic viewfinder; If it is determined in the determination step that the user is looking into the electronic viewfinder, control is performed so that the image captured by the first imaging means is displayed on the electronic viewfinder. a control step; 10. A method for controlling an imaging device, comprising:

12. 12. The control method for an imaging apparatus according to claim 11, wherein the determining step uses a trained model to determine whether or not a user is looking into the electronic viewfinder.

13. 13. The control method for an imaging device according to claim 12, wherein, after it is determined in the judgment step that the user is attempting to look through the electronic viewfinder, if a process for capturing an image and recording image data is executed using the first imaging means before a predetermined time has elapsed, the image data used in the judgment step to determine that the user is attempting to look through the electronic viewfinder is used as input data, and information indicating that the user is attempting to look through the electronic viewfinder is used as training data, and the learned model is re-trained.

14. the imaging device further comprises a display means having a display area larger than that of the electronic viewfinder; In the control step, If it is determined that the user is not looking into the electronic viewfinder, control is performed so that the image captured by the first imaging means is displayed on the display means; If it is determined in the determining step that the user is looking into the electronic viewfinder, control is performed so that the image captured by the first imaging means is not displayed on the display means.

12. The method for controlling an imaging apparatus according to claim 11.

15. A control method for an imaging device as described in Claim 11, characterized in that in the control step, a judgment is made in the judgment step depending on whether the face detected in the detection step satisfies a predetermined condition.

16. In the detecting step, facial feature points are detected from image data captured by the second imaging means, In the control step, control is performed so that the determination in the determination step is made in response to the feature points detected in the detection step satisfying the predetermined condition.

16. The method for controlling an imaging apparatus according to claim 15.

17. A storage step of storing image data captured by said second image capturing means from the time a face is detected in said detection step until said predetermined condition is satisfied, In the determining step, it is determined whether or not a user is looking into the electronic viewfinder based on the image data stored in the storing step.

16. The method for controlling an imaging apparatus according to claim 15.

18. In the detecting step, a person can be detected, In the storing step, storing of image data captured by the second imaging means is started in response to the detection of a person in the detecting step.

18. The method for controlling an imaging apparatus according to claim 17.

19. The control method for an imaging device described in Claim 17, characterized in that in the accumulation step, if a predetermined time has passed after a face is detected in the detection step without the predetermined condition being satisfied, the accumulated image data is erased.

20. A computer-readable program for causing a computer to execute the method for controlling an imaging apparatus according to any one of claims 11 to 19.

Images