DETECTION METHOD AND DETECTION DEVICE
First Claim
1. A computer-implemented detection method comprising:
- in response to inputting a first image including a region of one or more objects to a learned model, identifying a first entire image corresponding to entirety of a first object as a detection candidate, the learned model being generated by learning training data including an image corresponding to a part of an object and an entire image corresponding to entirety of the object;
detecting an existing region of the first target object in the first image in accordance with a comparison between the identified first entire image and the region of the one or more target objects; and
determining, based on a specific image obtained by invalidating the existing region in the first image, whether another target object is included in the first image.
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Abstract
A computer-implemented detection method includes, in response to inputting a first image including a region of one or more objects to a learned model, identifying a first entire image corresponding to entirety of a first object as a detection candidate, the learned model being generated by learning training data including an image corresponding to a part of an object and an entire image corresponding to entirety of the object, detecting an existing region of the first target object in the first image in accordance with a comparison between the identified first entire image and the region of the one or more target objects, and determining, based on a specific image obtained by invalidating the existing region in the first image, whether another target object is included in the first image.
12 Citations
12 Claims
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1. A computer-implemented detection method comprising:
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in response to inputting a first image including a region of one or more objects to a learned model, identifying a first entire image corresponding to entirety of a first object as a detection candidate, the learned model being generated by learning training data including an image corresponding to a part of an object and an entire image corresponding to entirety of the object; detecting an existing region of the first target object in the first image in accordance with a comparison between the identified first entire image and the region of the one or more target objects; and determining, based on a specific image obtained by invalidating the existing region in the first image, whether another target object is included in the first image. - View Dependent Claims (2, 3)
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4. The detection method according to claim, wherein
the detecting of the existing region includes determining the existing region based on a size of a difference between the first entire image and the region of the one or more target objects.
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5. A detection device comprising;
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a memory; and a processor coupled to the memory and the processor configured to; in response to inputting a first image including a region of one or more objects to a learned model, perform identification of a first entire image corresponding to entirety of a first object as a detection candidate, the learned model being generated by learning training data including an image corresponding to a part of an object and an entire image corresponding to entirety of the object, perform detection of an existing region of the first target object in the first image in accordance with a comparison between the identified first entire image and the region of the one or more target objects, and perform, based on a specific image obtained by invalidating the existing region in the first image, determination of whether another target object is included in the first image. - View Dependent Claims (6, 7, 8)
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9. A non-transitory computer-readable medium storing instructions executable by one or more computers, the instructions comprising:
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one or more instructions for identifying a first entire image corresponding to entirety of a first object as a detection candidate in response to inputting a first image including a region of one or more objects to a learned model, the learned model being generated by learning training data including an image corresponding to a part of an object and an entire image corresponding to entirety of the object; one or more instructions for detecting an existing region of the first target object in the first image in accordance with a comparison between the identified first entire image and the region of the one or more target objects; and one or more instructions for determining, based on a specific image obtained by invalidating the existing region in the first image, whether another target object is included in the first image. - View Dependent Claims (10, 11, 12)
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Specification