US-20260127870-A1 - IMAGE GENERATION APPARATUS, IMAGE RECOGNITION APPARATUS, AND IMAGE RECOGNITION METHOD

Abstract

An image generation apparatus including circuitry configured to acquire sensor data, and generate at least one output image in which recognition accuracy is reduced for at least one protection target in the acquired sensor data, wherein the recognition accuracy for the at least one protection target is reduced in each generated output image according to learning using a selected model to recognize a specified protection target corresponding to the at least one protection target.

Inventors

• Atsushi Irie
• LEO HOSHIKAWA
• Junji Otsuka
• Masakazu Yoshimura

Assignees

• Sony Group Corporation

Dates

Publication Date

20260507

Application Date

20240206

Priority Date

20230310

Claims (20)

1. 1 . An image generation apparatus comprising: circuitry configured to acquire sensor data, and generate at least one output image in which recognition accuracy is reduced for at least one protection target in the acquired sensor data, wherein the recognition accuracy for the at least one protection target is reduced in each generated output image according to learning using a selected model to recognize a specified protection target corresponding to the at least one protection target.
2. 2 . The image generation apparatus according to claim 1 , wherein the circuitry is configured to generate each output image in order to reduce the recognition accuracy for the at least one protection target within the output image by a parameter determined using at least one loss calculated based on a recognition score output by the selected model for the specified protection target.
3. 3 . The image generation apparatus according to claim 2 , wherein a type of the specified protection target is selected from among a plurality of types of protection targets in order to determine the selected model.
4. 4 . The image generation apparatus according to claim 3 , wherein the plurality of types of protection targets include one or more of a specific individual identity, a gender, an age, or a character similarity.
5. 5 . The image generation apparatus according to claim 3 , wherein the circuitry is further configured to adjust the determined parameter to adjust recognition accuracy for the specified protection target using the recognition score output by the selected model for the specified protection target when an input to the selected model includes one or more output images with reduced recognition accuracy.
6. 6 . The image generation apparatus according to claim 5 , wherein the circuitry is configured to adjust the determined parameter to increase recognition accuracy and reduce the recognition accuracy of the specified protection target.
7. 7 . The image generation apparatus according to claim 1 , wherein the circuitry is configured to generate the at least one output image in order to increase recognition accuracy of one or more objects in the acquired sensor data other than the at least one protection target, wherein the recognition accuracy is increased for the one or more objects in each generated output image according to one or more models different from the selected model, and wherein the one or more different models are trained to recognize the one or more objects corresponding to the one or more different models.
8. 8 . The image generation apparatus according to claim 1 , wherein the circuitry further comprises at least one image sensor configured to acquire the sensor data.
9. 9 . An image recognition apparatus comprising: circuitry configured to receive at least one output image in which recognition accuracy is reduced for at least one protection target in sensor data, and perform recognition related to the at least one protection target in the at least one output image, wherein the recognition accuracy for the at least one protection target is reduced in each generated output image according to learning using a selected model to recognize a specified protection target corresponding to the at least one protection target.
10. 10 . The image recognition apparatus according to claim 9 , wherein the recognition accuracy for the at least one protection target is reduced within the output image by a parameter determined using at least one loss calculated based on a recognition score output by the selected model for the specified protection target.
11. 11 . The image recognition apparatus according to claim 10 , wherein a type of the specified protection target is selected from among a plurality of types of protection targets in order to determine the selected model.
12. 12 . The image recognition apparatus according to claim 11 , wherein the type of the specified protection target is selected from the plurality of types of protection targets in accordance with a priority of each of the plurality of types of protection targets, a type of a task of performing recognition based on input data used in the learning, or a type of an application performing the task.
13. 13 . The image recognition apparatus according to claim 11 , wherein the type of the specified protection target is selected by a user from the plurality of types of protection targets.
14. 14 . The image recognition apparatus according to claim 11 , wherein the plurality of types of protection targets include one or more of a specific individual identity, a gender, an age, or a character similarity.
15. 15 . The image recognition apparatus according to claim 11 , wherein the determined parameter is adjusted to adjust the recognition accuracy for the specified protection target using the recognition score output by the selected model for the specified protection target when an input to the selected model includes one or more output images with reduced recognition accuracy.
16. 16 . The image recognition apparatus according to claim 15 , wherein the determined parameter is adjusted to increase recognition accuracy and reduce the recognition accuracy of the specified protection target.
17. 17 . The image recognition apparatus according to claim 9 , wherein the received at least one output image includes increased recognition accuracy of one or more objects in the sensor data other than the at least one protection target, wherein the recognition accuracy is increased for the one or more objects in each received output image according to one or more models different from the selected model, and wherein the one or more different models are trained to recognize the one or more objects corresponding to the one or more different models.
18. 18 . The image recognition apparatus according to claim 9 , wherein the circuitry is configured to perform recognition on a basis of the sensor data and a model obtained according to learning to increase accuracy of a task of performing recognition based on input data used in the learning.
19. 19 . The image recognition apparatus according to claim 18 , wherein the circuitry is configured to perform the task using a student model, and wherein the learning to reduce the recognition accuracy of the specified protection target and the learning to increase the accuracy of the task performed by the student model are performed using data obtained by a teacher model.
20. 20 . An image recognition method comprising: receiving at least one output image in which recognition accuracy is reduced for at least one protection target in sensor data; and performing recognition related to the at least one protection target in the at least one output image, wherein the recognition accuracy for the at least one protection target is reduced in each generated output image according to learning using a selected model to recognize a specified protection target corresponding to the at least one protection target.

Description

CROSS REFERENCE TO RELATED APPLICATIONS This application claims the benefit of Japanese Priority Patent Application JP 2023-037418 filed on Mar. 10, 2023, the entire contents of which are incorporated herein by reference. TECHNICAL FIELD The present disclosure relates to an image generation apparatus, an image recognition apparatus, and an image recognition method. BACKGROUND ART Various tasks of performing recognition on the basis of sensor data obtained by a sensor have been known. For example, examples of the sensor include a camera, and examples of the task include person detection based on an image captured by the camera. While it is possible to increase, by learning, the accuracy of recognition by the task, it may be necessary to protect the privacy of a person in a case where the sensor data contains a feature of the person. PTL 1 discloses a technique relating to learning based on an image information-reduced by tone reduction and contour extraction. According to such a technique, it is possible to obtain an image that allows protection of the privacy of a person while increasing the accuracy of recognition by the task. Furthermore, NPL 1 discloses a technique of generating an image using a model obtained as a result of performing learning to reduce the accuracy of recognition. According to such a technique, it is possible to obtain an image that allows protection of the privacy of a person. NPL 2 also discloses a technique of disabling recognition based on an image only in a case where a specific device such as a specific camera or a specific image signal processor (ISP) is used. According to such a technique, it is possible to protect the privacy of a person appearing in the image. CITATION LIST Patent Literature PTL 1: JP 2022-96519 A Non Patent Literature NPL 1: Ali Shahin Shamsabadi, et al. “EdgeFool: An Adversarial Image Enhancement Filter”, [online], [searched on Feb. 1, 2023], Internet <https://arxiv.org/pdf/1910.12227.pdf>NPL 2: Buu Phan, et al. “Adversarial Imaging Pipelines”, [online], [searched on Feb. 1, 2023], Internet <https://arxiv.org/pdf/2102.03728.pdf> SUMMARY Technical Problem Examples of the protection target, however, include a plurality of types of features such as the gender and age of a person. Then, there is also a possibility that it is desired to protect a specific feature among a plurality of types of features. It is therefore desirable to perform learning to reduce the accuracy of recognition of a specific protection target. Solution to Problem According to the present disclosure, there is provided an image generation apparatus that includes circuitry configured to acquire sensor data, and generate at least one output image in which recognition accuracy is reduced for at least one protection target in the acquired sensor data, wherein the recognition accuracy for the at least one protection target is reduced in each generated output image according to learning using a selected model to recognize a specified protection target corresponding to the at least one protection target. Furthermore, according to the present disclosure, there is provided an image recognition apparatus that includes circuitry configured to receive at least one output image in which recognition accuracy is reduced for at least one protection target in sensor data, and perform recognition related to the at least one protection target in the at least one output image, wherein the recognition accuracy for the at least one protection target is reduced in each generated output image according to learning using a selected model to recognize a specified protection target corresponding to the at least one protection target. In addition, according to the present disclosure, there is provided an image recognition method including receiving at least one output image in which recognition accuracy is reduced for at least one protection target in sensor data, and performing recognition related to the at least one protection target in the at least one output image, wherein the recognition accuracy for the at least one protection target is reduced in each generated output image according to learning using a selected model to recognize a specified protection target corresponding to the at least one protection target. BRIEF DESCRIPTION OF DRAWINGS FIG. 1 is a diagram for describing a typical recognition system. FIG. 2 is a diagram for describing a first example of privacy information that can be a protection target. FIG. 3 is a diagram for describing a second example of the privacy information that can be the protection target. FIG. 4 is a diagram for describing a third example of the privacy information that can be the protection target. FIG. 5 is a diagram for describing an example of image generation according to a comparative example. FIG. 6 is a diagram for describing an example of image generation according to an embodiment of the present disclosure. FIG. 7 is a diagram for describing a first example of a loss