Information processing system, image processing method, and image processing program

Abstract

To improve user experiences.SOLUTION: An information processing apparatus includes: a feature detection unit which detects, in an image captured by a camera, a feature region based on features related to a person; a frame setting unit 32 which virtually sets a plurality of frames in the image in accordance with the detected feature region; a frame selection unit 33 which selects a frame of interest, based on a predetermined condition, as a frame of interest, out of the frames; and an image output unit 34 which outputs the image of interest as a highlighted image which is to be highlighted.SELECTED DRAWING: Figure 3

Description

[Technical Field]

[0001] The present disclosure relates to an information processing system, an image processing method, and an image processing program. [Background technology]

[0002] In recent years, web conferences have become more frequent, and camera modules with functions suited to web conferences have been proposed. For example, camera modules with built-in VPUs (Visual Processing Units) that automatically adjust the framing (adjust the viewing angle) have been proposed to enable more natural web conferences.

[0003] Such camera modules detect the position of people in the image, identify regions of interest (ROIs) such as speakers within the image, and perform auto-framing (automatic adjustment of pan, tilt, and zoom) to highlight those regions of interest. Summary of the Invention [Problem to be solved by the invention]

[0004] With conventional auto-framing, for example, in a meeting with multiple people in the image, where the speaker changes frequently, auto-framing is performed seamlessly each time the speaker changes. This image is as if the meeting were filmed with a single camera, and the camera zooms in to follow the frequently changing speakers, which can result in excessive changes in the image and a poor user experience.

[0005] The present disclosure has been made in consideration of the above circumstances, and aims to provide an information processing system, an image processing method, and an image processing program that can improve the user experience. [Means for solving the problem]

[0006] An information processing system according to one aspect of the present disclosure includes a feature detection unit that detects a feature region based on features related to a person in an image acquired by a camera; a frame setting unit that virtually sets a plurality of frames in the image according to the detected feature region; a frame selection unit that selects a frame of interest from the plurality of frames based on a predetermined condition as a frame of interest; and a frame selection unit that selects the frame of interest and the frame of interest as an emphasis image to be highlighted. In the image and an image output unit that outputs an image of the frame of interest, which is an image area surrounded by the frame of interest.

[0007] An image processing method according to one aspect of the present disclosure includes: detecting, in an image captured by a camera, a characteristic region based on characteristics of a person; virtually setting a plurality of frames in the image according to the detected characteristic region; selecting a frame of interest from the plurality of frames based on a predetermined condition as a frame of interest; and selecting the frame of interest and the frame of interest as an enhanced image to be displayed in a highlighted manner. In the image An image of the frame of interest, which is an image area surrounded by the frame of interest, is output.

[0008] One aspect of the present disclosure is an image processing program for causing a computer to execute the image processing method. [Effects of the Invention]

[0009] The information processing system, image processing method, and image processing program disclosed herein have the effect of improving the user experience. [Brief explanation of the drawings]

[0010] [Figure 1] 1 is a system configuration diagram illustrating an outline of a system configuration of a Web conference system according to an embodiment of the present disclosure. [Figure 2] 1 is a schematic configuration diagram illustrating an example of a hardware configuration of an information processing device according to an embodiment of the present disclosure. [Figure 3]FIG. 2 is a functional configuration diagram illustrating an example of an image processing function included in an information processing device according to an embodiment of the present disclosure. [Figure 4] FIG. 2 illustrates an example of an image captured by a camera according to an embodiment of the present disclosure. [Figure 5] FIG. 2 is a diagram illustrating a function of a face detection unit according to an embodiment of the present disclosure. [Figure 6] FIG. 10 is a diagram illustrating a frame setting method according to an embodiment of the present disclosure. [Figure 7] FIG. 10 is a diagram illustrating a frame setting method according to an embodiment of the present disclosure. [Figure 8] 10A and 10B are diagrams for explaining a frame adjustment method according to an embodiment of the present disclosure. [Figure 9] 10A and 10B are diagrams for explaining a frame adjustment method according to an embodiment of the present disclosure. [Figure 10] FIG. 10 is a diagram illustrating an example of a display screen according to an embodiment of the present disclosure. [Figure 11] 1 is a flowchart illustrating an example of a processing procedure of an image processing method according to an embodiment of the present disclosure. DETAILED DESCRIPTION OF THE INVENTION

[0011] An information processing system, an image processing method, and an image processing program according to an embodiment of the present disclosure will be described below with reference to the drawings. An information processing device 10 will be described as an example of the information processing system.

[0012] 1 is a system configuration diagram that schematically illustrates the system configuration of a Web conference system 1 according to an embodiment of the present disclosure. As shown in FIG. 1, a plurality of information processing devices 10 and a conference server 50 are connected to a network 5. Examples of the information processing devices 10 include desktop PCs, all-in-one PCs in which a display and a main body are integrated, notebook PCs, tablet terminals, and smartphones. Although three information processing devices 10 are shown in the example shown in FIG. 1, the number of connected information processing devices is not limited to this.

[0013] Fig. 2 is a schematic diagram showing an example of the hardware configuration of an information processing device 10 according to this embodiment. As shown in Fig. 2, the information processing device 10 includes, for example, a CPU (Central Processing Unit: processor) 11, a main memory 12, a secondary storage (memory) 13, an external interface 14, and a communication interface 15. These components are interconnected directly or indirectly via a bus 21, and cooperate with each other to execute various processes. The information processing device 10 may also include an input device 16 and an output device 17. The information processing device 10 may also include a speaker 18, a microphone 19, and a camera 20. The input device 16, the output device 17, the speaker 18, the microphone 19, and the camera 20 may all be mounted on the main body of the information processing device 10, or may be provided as external devices connected via the external interface 14 or the communication interface 15.

[0014] The CPU 11 controls the entire information processing device 10 using, for example, an OS (Operating System) stored in a secondary storage device 13 connected via a bus 21, and executes various processes by executing various programs stored in the secondary storage device 13. One or more CPUs 11 may be provided, and they may work together to realize processes.

[0015] The main memory device 12 is composed of writable memory such as cache memory and RAM (Random Access Memory), and is used as a working area for reading out programs executed by the CPU 11 and writing data processed by the programs.

[0016] The secondary storage device 13 is a non-transitory computer-readable storage medium. Examples of the secondary storage device 13 include a magnetic disk, a magneto-optical disk, a CD-ROM, a DVD-ROM, and a semiconductor memory. Examples of the secondary storage device 13 include a read-only memory (ROM), a hard disk drive (HDD), and a solid-state drive (SSD) flash memory. The secondary storage device 13 stores, for example, an operating system (OS) for controlling the entire information processing device 10, such as Windows (registered trademark), iOS (registered trademark), or Android (registered trademark), a basic input / output system (BIOS), various device drivers for operating peripheral devices, various application software, and various data and files. The secondary storage device 13 also stores programs for implementing various processes and various data required for implementing the various processes. A plurality of secondary storage devices 13 may be provided, and the programs and data described above may be stored separately in each secondary storage device 13.

[0017] The external interface 14 is an interface for connecting to an external device. Examples of external devices include an external monitor, a USB memory, an external HDD / SSD, an external camera, and an external audio device. Although only one external interface is shown in the example of FIG. 2, multiple external interfaces may be provided. Examples of interface standards for external monitors include DisplayPort, HDMI (registered trademark) (High-Definition Multimedia Interface), DVI (Digital Visual Interface), and VGA (Video Graphics Array).

[0018] The communication interface 15 functions as an interface for connecting to a network to communicate with other devices and transmitting and receiving information. For example, the communication interface 15 communicates with other devices via a wired or wireless connection. Examples of wireless communication include communication via lines such as Bluetooth (registered trademark), Wi-Fi, mobile communication systems (3G, 4G, 5G, 6G, LTE, etc.), and wireless LAN. An example of wired communication is communication via lines such as a wired LAN (Local Area Network).

[0019] The input device 16 is a user interface for a user to perform input operations, and examples thereof include a keyboard, a touchpad, a pointing device, etc. Examples of pointing devices include a mouse, a touch panel, a pen tablet, a trackpad, a trackball, etc. Examples of output devices include a display and a projector.

[0020] The speaker 18 converts audio data into sound and outputs it. The microphone 19 converts sound into audio data, which is an electrical signal, and outputs it. The speaker 18 and the microphone 19 may be provided separately, or may be provided as an integrated sound system.

[0021] The camera 20 includes, for example, a lens, a lens driver, and an image sensor. The lens captures light from a subject and forms an image of the subject on the image sensor. The image sensor converts the light captured by the lens into signal charges to capture the subject image. The image sensor generates an analog image signal by capturing, for example, red (R), green (G), and blue (B) signal values ​​in an order corresponding to a Bayer array, and converts the resulting image signal from analog to digital to generate image data (RAW data). The image data (RAW data) is then subjected to various signal processing processes, such as automatic exposure adjustment, automatic white balance adjustment, matrix processing, edge enhancement, brightness compression, and gamma processing, and the processed image data is output. The image data (RAW data) may be output from the camera 20, and the signal processing may be performed by a processor such as the CPU 11.

[0022] The conference server 50 is a general-purpose PC, and like the information processing device 10 described above, is equipped with a CPU, a main storage device, a secondary storage device, a communication interface, etc. The conference server 50 has various data, applications, etc. necessary for providing a Web conference, and a Web conference is realized by each information processing device 10 connecting to the conference server 50 via the network 5. Since many known techniques have been proposed for realizing a Web conference, it is sufficient to adopt these known techniques as appropriate.

[0023] Next, an example of image processing functions of the information processing device 10 according to this embodiment will be described with reference to the drawing. Fig. 3 is a functional block diagram showing an example of image processing functions of the information processing device 10 according to this embodiment.

[0024] A series of processes for realizing various functions described below is stored in the form of a program (e.g., an image processing program) in the secondary storage device 13 or the like provided in each information processing device 10, and the CPU (processor) 11 reads this program into the main storage device 12 and executes information processing and arithmetic processing to realize various functions. For example, the image processing program may be implemented in an application that runs a web conference. The image processing program may be pre-installed in the secondary storage device 13, provided in a state stored in another computer-readable storage medium, or distributed via wired or wireless communication means, etc. Examples of computer-readable storage media include magnetic disks, magneto-optical disks, CD-ROMs, DVD-ROMs, and semiconductor memories.

[0025] As shown in FIG. 3, the image processing unit 30 includes a feature detection unit, a frame setting unit 32, a frame selection unit 33, and an image output unit . The feature detection unit detects feature regions based on features related to a person in an image acquired by the camera 20. For example, a face detection unit 31 is an example of a feature detection unit. The face detection unit 31 detects faces (specifically, facial regions, hereinafter referred to as "facial regions") included in the image acquired by the camera 20. For example, the face detection unit 31 extracts facial feature points included in the image and detects facial regions using the extracted feature points. Note that many known techniques have been proposed for detecting facial regions, and any of these known techniques may be appropriately adopted. As a result, for example, when the image 40 shown in FIG. 4 is acquired by the camera 20, five facial regions FC are detected as shown in FIG. 5.

[0026] In this embodiment, a face detection unit is used as an example of the feature detection unit, but this is not limiting. For example, the feature detection unit may have a function of detecting features related to a person in an image and detecting a feature region based on the detected features. For example, the features related to a person are not limited to facial features, but may be other features (e.g., head, upper shoulders, upper body, whole body, etc.). For example, the feature detection unit may detect a feature region in an image according to a pre-registered algorithm based on the positions and / or sizes of features related to a person detected in the image (e.g., eyes, nose, head, shoulders, arms, etc.).

[0027] The frame setting unit 32 virtually sets multiple frames FR within the image 40 according to the face areas FC detected within the image 40. In other words, the frames FR are virtually set in processing within the information processing device 10. The set virtual frames FR may also be displayed as images on the output device 17. In this case, the frame setting unit 32 may set the frames FR so that each face area FC is included in one of the frames FR, and so that each face area FC is not included in multiple frames FR (excluding the entire frame, which will be described later).

[0028] For example, the frame setting unit 32 has default information. The default information includes, for example, the number of frames to be set in the image 40. Specifically, the default information includes the number of frames to be set in the image 40, and the default size and default position of each frame.

[0029] For example, the frame setting unit 32 has a plurality of modes, and has frame default information for each mode. Examples of modes include a meeting mode and a conference mode. Here, the meeting mode may be further set to a plurality of modes depending on the number of people (i.e., the number of face areas). Examples include a small-scale meeting mode for four people or less, a large-scale meeting mode for five to eight people, and a group meeting mode for multiple groups to discuss. The conference mode applies when the number of people is nine or more.

[0030] The above-mentioned mode may be selected by the user, or may be automatically determined based on image features, including at least one of the number of face regions FC, the distance from the camera 20 to the person (in other words, the size of the face in the image), the position of furniture such as a table in the image, and the arrangement of the face regions FC.

[0031] The configuration may also be such that modes can be customized. For example, the positions of tables and chairs in a conference room are somewhat fixed. Furthermore, since the installation position of the camera 20 is often relatively stable, the angle of view is also somewhat fixed. Therefore, a configuration may be such that images of the conference room and custom modes can be registered in advance in association with each other. When selecting a mode, the frame setting unit 32 may compare the image acquired by the camera 20 with images previously registered for each custom mode, and select a mode based on the degree of correspondence between the two images. By setting the priority of the custom mode higher than the above-mentioned modes (hereinafter referred to as "general modes"), it may first be determined whether the mode corresponds to a custom mode, and if there is no corresponding custom mode, the mode may be identified from the above-mentioned general modes.

[0032] When the frame setting unit 32 identifies one of the multiple modes, it acquires default information associated with the identified mode and sets a default frame FR within the image based on the acquired default information. As a result, for example, as shown in FIG. 6, a frame FR of a default size is set at a default position in the image 40. In FIG. 6, as an example, frames FR(C), FR(R), and FR(L) are set as defaults at the center, right, and left, respectively, within the image 40. In the following description, when there is no need to distinguish between the center, right, and left frames, they will be referred to as frames FR; when they are distinguishable, they will be referred to as right frame FR(R), center frame FR(C), and left frame FR(L). For convenience of explanation, in FIG. 6 and other figures, the frame FR is visualized, but the frame FR may be virtually set information. The same applies to the face area FC described above.

[0033] Next, the frame setting unit 32 sets multiple frames FR within the image 40 by moving and resizing each set frame FR according to the facial area FC included in the image 40. For example, the position and size are adjusted so as to encompass all of the facial areas FC included in each frame FR set at a default position. Here, the size is adjusted so that the aspect ratio (width to height ratio) of each frame FR becomes a preset value. As a result, for example, a frame FR as shown in FIG. 7 is set within the image 40. Furthermore, an entire frame FR(LS) that encompasses all of the facial areas FC within the image 40 may be additionally set.

[0034] The frame setting unit 32 may adjust or reset the frame FR when a predetermined event occurs. For example, the frame setting unit 32 may adjust or reset the frame FR when the number of faces in the image 40 changes or the number of faces in each frame FR changes.

[0035] For example, as shown in FIG. 8, if the number of people in the image 40 changes due to an increase in the number of faces during a meeting, the frame setting unit 32 adjusts at least one frame FR so that the added face area FC is included in one of the frames FR. FIG. 8 illustrates an example in which a person is added to the front left side of the image 40. In this case, the left frame FR(L) closest to the added person is identified, and the identified left frame FR(L) is expanded to include the added face area FC, thereby adjusting the left frame FR(L). As a result, as shown in FIG. 9, the left frame FR(L) is expanded, and the entire frame FR(LS) is also expanded. At this time, it is preferable that the aspect ratio of the frame FR be maintained before and after the adjustment. Note that instead of readjustment, the frame FR may be reset.

[0036] The frame selection unit 33 identifies a frame FR of interest from among the multiple frames FR based on predetermined selection conditions as a frame of interest. For example, the frame selection unit 33 selects a frame FR that includes a speaker as a frame of interest. One example of a speaker identification method is to use Direction of Arrival (DOA) information, which is a well-known technique. Specifically, the speaker analyzes the sound arrival direction based on audio data acquired by the microphone 19, and selects a frame FR that matches the arrival direction as a frame of interest. The speaker may also be identified based on the mouth movement, gesture size, etc. of a face area FC in the image 40. It should be noted that a number of known techniques have been proposed for identifying speakers, and any of these known techniques may be appropriately adopted.

[0037] If there are multiple frames FR that satisfy the selection conditions, the frame selection unit 33 selects the multiple frames that satisfy the selection conditions as frames of interest. Specifically, if multiple people are speaking at the same time, all frames FR that include the speakers are selected as frames of interest. If there is no speaker, the frame selection unit 33 selects the entire frame FR(LS) as the frame of interest.

[0038] The above-described conditions for selecting a frame of interest are merely examples, and may be set appropriately depending on the application. For example, the frame of interest may be switched sequentially at a predetermined time interval among a plurality of frames FR, regardless of who is speaking. Furthermore, when there is no speaker, instead of selecting the entire frame, the right frame FR(R), center frame FR(C), and left frame FR(L) may be switched sequentially at a predetermined time interval and selected as the frame of interest.

[0039] The image output unit 34 outputs the image of the frame of interest as an emphasized image to be highlighted. As a result, for example, when the frame of interest is changed, the emphasized image is switched in accordance with the change of the frame of interest. For example, in the image 40 shown in FIG. 7, when the frame of interest is changed from the right frame FR(R) to the left frame FR(L), the image output unit 34 outputs the image of the left frame FR(L) instead of the image of the right frame FR(R) that had been output as the emphasized image until then. The emphasized image is transmitted, for example, together with audio data acquired by the microphone 19, to the conference server 50 via the network 5 (see FIG. 1), and is further transmitted via the conference server 50 to the information processing device 10 participating in the Web conference. As a result, an image in which the emphasized image is emphasized is displayed on the display screen of the information processing device 10, for example, as shown in FIG. 10. Note that in the screen example shown in FIG. 10, the emphasized image is superimposed on the image of the whole frame FR(LS), but the screen example is not limited to this, and may be any mode in which the emphasized image is displayed in a more emphasized manner than other images.

[0040] Next, an image processing method executed by the information processing device 10 will be described with reference to Fig. 11. Fig. 11 is a flowchart showing an example of the processing procedure of the image processing method according to this embodiment. For example, the following processing is started when a web conference application is launched and the camera 20 is turned on, and after starting, is repeatedly executed at predetermined time intervals or for every predetermined number of image frames input from the camera 20. Then, it ends when the web conference application is ended or the camera 20 is turned off.

[0041] 11, first, image data is acquired from the camera 20 (SA1), and then the frame FR is initialized. In the initialization of the frame FR, a face area FC included in an image 40 based on the image data is detected (SA2). Next, a mode is identified based on the detected face area FC and the characteristics of the image 40 (SA3), and the frame FR is set as a default within the image 40 based on default information associated with the mode (SA4). Next, the position and size of the frame FR are adjusted based on the face area FC included in the image 40, and the frame FR is set (SA5).

[0042] Once the frame has been initialized in this way, a frame of interest is selected based on predetermined conditions (SA6). For example, if a speaker is present, a frame containing the speaker is selected as the frame of interest. At this time, if there are multiple frames containing the speaker, multiple frames are selected as the frame of interest. Furthermore, if there is no speaker, for example, the entire frame FR(LS) is selected as the frame of interest. Subsequently, the image of the frame of interest is output as an enhanced image (SA7). At this time, if multiple frames of interest are selected, an image may be generated by merging the images of the selected multiple frames of interest, and the generated image may be output as the enhanced image.

[0043] As a result, for example, image data of the emphasized image is transmitted to the conference server 50 (see FIG. 1) via the network 5 together with audio data acquired by the microphone 19, and further transmitted to each information processing device 10 participating in the Web conference via the conference server 50. As a result, for example, an image in which the image of the frame of interest is emphasized as shown in FIG. 10 is displayed on the display screen of the information processing device 10 participating in the Web conference.

[0044] Next, image data captured by camera 20 is acquired (SA8), and it is determined whether image 40 based on the acquired image data satisfies the conditions for frame adjustment (SA9). For example, it is determined whether the number of facial areas FC included in image 40 has increased or decreased, or whether the number of facial areas FC included in each frame FR has increased or decreased. As a result, if either condition is met, it is determined that the conditions for frame adjustment are met (SA9: YES), and frame adjustment is performed (SA10). On the other hand, if the conditions for frame adjustment are not met (SA9: NO), it is determined that frame adjustment is not necessary, and the process returns to step SA6, and the subsequent processes are repeated.

[0045] By repeating the processes from step SA6 onwards, if the speaker changes and the frame of interest is changed, the image of the changed frame of interest is output as an emphasized image. As a result, for example, the image of the speaker (emphasized image) is switched and displayed on the display screen of the information processing device 10 participating in the Web conference.

[0046] As described above, the information processing system (information processing device 10), image processing method, and image processing program according to this embodiment set multiple frames FR based on a facial area FC included in an image 40, select a frame of interest from the multiple frames FR based on predetermined conditions, and output the image of the selected frame of interest as an enhanced image. As a result, for example, an image of a frame including a speaker is displayed on the display screen of each information processing device 10 participating in the web conference, switching as the speaker changes. This makes it possible to provide a stable image with reduced image wobble compared to conventional methods, improving the user experience.

[0047] Although the present disclosure has been described above using embodiments, the technical scope of the present disclosure is not limited to the scope described in the above embodiments. Various settings or improvements can be made to the above embodiments without departing from the gist of the disclosure, and forms with such settings or improvements are also included in the technical scope of the present disclosure. Furthermore, the processing flow described in the above embodiment is also an example, and unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged within the scope of the present disclosure.

[0048] For example, in the above-described embodiment, the emphasized image is switched when the frame of interest is switched, but instead of switching the emphasized image, a display mode in which the camerawork gradually moves from the emphasized image before the switch to the emphasized image after the switch may be used. 10 is an example, and the display mode of the emphasized image is not limited to this. For example, the display screen may be divided into two or more areas, and the emphasized image may be displayed in one of the areas, and the image of the whole frame FR(LS) may be displayed in the other areas.

[0049] In the above embodiment, when the frame of interest is changed and the changed frame of interest is maintained for a predetermined period of time, the image output unit 34 may output the image of the frame of interest as an emphasized image. This makes it possible to prevent the output image from changing due to frequent changes in the frame of interest, and allows each information processing device 10 to display a stable image.

[0050] Furthermore, in the above-described embodiment, the case where the information processing device 10 has the functions of the image processing unit 30 has been described, but this is not limiting. For example, some of the functions of the image processing unit 30 may be provided in the camera 20. Furthermore, the DOA function used by the frame selection unit 33 to identify the speaker may be provided in the microphone 19. In this case, DOA information is acquired from the microphone 19, and the frame of interest is identified.

[0051] The image processing unit 30 may also be provided in the conference server 50. In this case, the image data acquired by the camera 20 and the audio data acquired by the microphone 19 are transmitted to the conference server 50 via the network 5. The image processing unit 30 of the conference server 50 executes the image processing method described above based on the received image data, and transmits the image data and audio data including the enhanced image to each information processing device 10. This allows the web conference to be held smoothly. [Explanation of symbols]

[0052] 1: Web conferencing system 5: Network 10: Information processing device 11: CPU 12: Main memory 13:Secondary storage device 14: External interface 15: Communication interface 16: Input device 17: Output device 18: Speaker 19:Mike 20: Camera 21: Bus 30: Image processing section 31: Face detection unit 32: Frame setting section 33: Frame selection section 34: Image output unit 40: Image 50: Conference server FC: Face area FR: Frame FR(C): Center frame FR(R): Right frame FR(L): Left frame FR(LS): Full frame

Claims

1. a feature detection unit that detects a feature region based on features related to a person in an image acquired by a camera; a frame setting unit that virtually sets a plurality of frames within the image in accordance with the detected characteristic region; a frame selection unit that selects a frame of interest from the plurality of frames based on a predetermined condition; an image output unit that outputs, as an emphasized image to be emphasized, an image of the frame of interest, which is the frame of interest and an image area within the image surrounded by the frame of interest; An information processing system comprising:

2. The frame setting unit 2. The information processing system according to claim 1, further comprising default information associated with a plurality of modes, the default information including the number of frames to be set in an image.

3. the frame setting unit identifies one of the modes based on the characteristics of the image; The information processing system according to claim 2 , wherein the image features include at least one of the number of face regions, the size of the face regions in the image, the position of furniture in the image, and the arrangement of the face regions.

4. The default information includes the number of frames to be set in the image, and a default size and a default position of each of the frames; The information processing system of claim 2, wherein the frame setting unit identifies one of the modes according to the characteristics of the image, virtually sets multiple frames of default size and default position within the image based on default information corresponding to the identified mode, and virtually sets multiple frames within the image by moving and adjusting the size of each of the set frames according to a facial area contained in the image.

5. The information processing system according to claim 1 , wherein the frame setting unit adjusts or resets the frame when a predetermined event occurs.

6. The information processing system according to claim 1 , wherein the frame setting unit adjusts or resets the frames when the number of face regions in the image or the number of face regions in each of the frames changes.

7. The information processing system according to claim 1 , wherein the frame setting unit sets the frames so that each face area is included in one of the frames, and so that each face area is not included in multiple of the frames.

8. The computer Detecting a feature region based on features related to a person in an image acquired by a camera; Virtually setting a plurality of frames within the image according to the detected feature region; selecting a frame of interest from the plurality of frames based on a predetermined condition as a frame of interest; An image processing method for outputting, as an emphasized image to be displayed in an emphasized manner, an image of the frame of interest, which is the frame of interest and an image area within the image surrounded by the frame of interest.

9. An image processing program for causing a computer to execute the image processing method according to claim 8.

Images