US 12,464,237 B2
Inference apparatus, image capturing apparatus, training apparatus, inference method, training method, and storage medium
Hideyuki Hamano, Kanagawa (JP); Akihiko Kanda, Kanagawa (JP); Kuniaki Sugitani, Kanagawa (JP); and Yohei Matsui, Kanagawa (JP)
Assigned to CANON KABUSHIKI KAISHA, Tokyo (JP)
Filed by CANON KABUSHIKI KAISHA, Tokyo (JP)
Filed on Feb. 15, 2024, as Appl. No. 18/442,261.
Claims priority of application No. 2023-024624 (JP), filed on Feb. 20, 2023.
Prior Publication US 2024/0284047 A1, Aug. 22, 2024
Int. Cl. H04N 23/67 (2023.01); G06T 7/50 (2017.01); H04N 23/61 (2023.01); H04N 23/63 (2023.01)
CPC H04N 23/675 (2023.01) [G06T 7/50 (2017.01); H04N 23/61 (2023.01); H04N 23/635 (2023.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30196 (2013.01); H04N 23/672 (2023.01)] 21 Claims
OG exemplary drawing
 
1. An image capturing apparatus comprising at least one processor and/or at least one circuit which functions as:
an image capturing unit configured to generate an image through shooting;
a first detection unit configured to detect a subject region from the image;
a second detection unit configured to detect a plurality of distance information pieces from a plurality of focus detection regions inside the subject region; and
an inference unit configured to perform inference with use of a machine learning model based on the subject region including a subject within the image obtained through shooting, and on the plurality of distance information pieces detected from the plurality of focus detection regions inside the subject region, thereby generating an inference result indicating a distance information piece corresponding to the subject or a distance information range corresponding to the subject,
wherein the machine learning model is a model that has been trained to suppress a contribution made to the inference result by one or more distance information pieces that are not based on the subject among the plurality of distance information pieces.