State estimation device, state estimation method, and state estimation program

A state estimation method performed by a computer, the method comprising:

• estimating first feature amount data from input image data with a first object estimation model subjected to machine learning to estimate the first feature amount data obtained by estimating a feature amount of a first extraction target from input first image data by using first teacher data comprising the first image data obtained by an imaging device having imaged a traffic environment and first correct value data of the first extraction target comprising a moving object in the first image data;
• estimating second feature amount data from input image data with a second object estimation model subjected to machine learning to estimate the second feature amount data obtained by estimating the feature amount of the first extraction target from the input first image data by using second teacher data comprising second image data obtained by an imaging device having imaged a traffic environment and second correct value data of a second extraction target comprising a road in the second image data;
• estimating installation state parameters of an imaging device having obtained the input image data by imaging by using the first feature amount data and the second feature amount data with a state estimation model subjected to machine learning to estimate the installation state parameters of the imaging device having obtained the input image data by imaging by using third teacher data comprising image data obtained by the imaging device having imaged a traffic environment and correct value data of the installation state parameters of the imaging device having obtained the image data by imaging;
• and
• diagnosing an installation state of the imaging device based on the estimated installation state parameters.

A non-transitory computer-readable medium storing a state estimation program causing a computer to execute

• estimating first feature amount data from input image data with a first object estimation model subjected to machine learning to estimate the first feature amount data obtained by estimating a feature amount of a first extraction target from input first image data by using first teacher data comprising the first image data obtained by an imaging device having imaged a traffic environment and first correct value data of the first extraction target comprising a moving object in the first image data;
• estimating second feature amount data from input image data with a second object estimation model subjected to machine learning to estimate the second feature amount data obtained by estimating the feature amount of the first extraction target from the input first image data by using second teacher data comprising second image data obtained by an imaging device having imaged a traffic environment and second correct value data of a second extraction target comprising a road in the second image data;
• estimating installation state parameters of an imaging device having obtained the input image data by imaging by using the first feature amount data and the second feature amount data with a state estimation model subjected to machine learning to estimate the installation state parameters of the imaging device having obtained the input image data by imaging by using third teacher data comprising image data obtained by the imaging device having imaged a traffic environment and correct value data of the installation state parameters of the imaging device having obtained the image data by imaging;
• and
• diagnosing an installation state of the imaging device based on the estimated installation state parameters.