Abstract: A difference detection device includes a difference detection unit configured to, based on association among a first image and a second image captured at different times and illustrating a substantially identical space and encoding information of each of the first image and the second image, detect difference between a third image and a fourth image captured at different times and illustrating a substantially identical space, and the encoding information is information acquired from data including the first image encoded and data including the second image encoded, before inverse transform processing is executed in decoding processing executed on each of the first image and the second image.

Abstract: A learning data generation device of an embodiment includes a detection unit that detects a changed region in a space between a first map and a second map based on first map data which indicate the first map and second map data which indicate the second map which indicates a substantially same space as the first map and represents the space at a different time point from the first map and a changed region image acquisition unit that acquires images which correspond to the changed region detected by the detection unit from a first image in which the space represented by the first map is captured and a second image in which the space represented by the second map is captured.

Abstract: A deep feature generation unit (20) inputs an inference image from an input layer (21) of a neural network, performs forward propagation in the neural network, and outputs a plurality of frame images that each include a channel image and are aligned in a predetermined first sequence as intermediate output values from an intermediate layer (22), which is a predetermined layer that is not an output layer of the neural network. A rearrangement unit (30) rearranges the frame images aligned in the first sequence into frame images in a second sequence based on a predetermined rearrangement sequence from the first sequence to the second sequence, such that a total of degrees of similarity between adjacent frame images in the second sequence is greater than a total of degrees of similarity between adjacent frame images in the first sequence.

Abstract: An image processing device includes an image processing unit configured to execute image processing on an image based on an input image and output a result of the image processing, the input image is a post-conversion image obtained by performing image conversion on an original image, and the conversion includes image conversion for further decreasing a data size of the original image while maintaining a feature quantity used in the image processing and processing accuracy of the image processing.

Abstract: An abnormality determination device includes: an analysis unit that analyzes at least a feature amount related to a pattern of a captured image of a manhole cover, the feature amount being included in coded information obtained by coding the captured image; and a determination unit that determines based on an analysis result of the analysis unit whether the manhole cover is abnormal.

Abstract: A position determination apparatus for determining, from a first image that is an image including at least a desired first subject, a position of the desired first subject, includes: a feature amount acquisition unit that acquires a first feature amount representing a predetermined feature of the first image; an estimation unit in which a second feature amount representing the predetermined feature obtained from a second image including a second subject is associated with a selected feature map that is a feature map corresponding to the second subject among a plurality of feature maps that are a set of feature maps that are maps representing features of the second image; an estimated first feature map that is estimated by the estimation unit to be associated with the first feature amount: and a position determination unit that determines the position of the desired first subject using the estimated first feature map.

Abstract: An image processing device includes an image processing unit configured to execute image processing on an image based on an input image, and output a result of the image processing. The input image is a post-conversion image obtained by performing image conversion on an original image. The image conversion includes image conversion for further reducing a data size of the original image while maintaining a feature acquired from the original image and related to an object similar to a subject captured in the original image and maintaining processing accuracy of the image processing.

Abstract: A difference detection apparatus includes: an acquisition unit configured to acquire a difference level indicating a level of a difference between a first image that is an image of a first spatial region and a second image that is an image of a second spatial region located at a substantially same position as the first spatial region, first probability data indicating a probability that a target object is present in the first spatial region, and second probability data indicating a probability that the target object is present in the second spatial region; and a detection unit configured to associate the difference level, the first probability data, and the second probability data, and detect, based on a result of the association, a region where a difference occurs between the first image and the second image.

Abstract: An image processing device includes an image processing unit configured to execute image processing on an image based on an input image and output a result of the image processing, the input image is a post-conversion image obtained by performing image conversion on an original image, and the conversion includes image conversion for further decreasing a data size of the original image while maintaining a feature quantity used in the image processing and processing accuracy of the image processing.

Abstract: A difference detection device includes a difference detection unit configured to, based on association among a first image and a second image captured at different times and illustrating a substantially identical space and encoding information of each of the first image and the second image, detect difference between a third image and a fourth image captured at different times and illustrating a substantially identical space, and the encoding information is information acquired from data including the first image encoded and data including the second image encoded, before inverse transform processing is executed in decoding processing executed on each of the first image and the second image.

Abstract: A learning data generation device of an embodiment includes a detection unit that detects a changed region in a space between a first map and a second map based on first map data which indicate the first map and second map data which indicate the second map which indicates a substantially same space as the first map and represents the space at a different time point from the first map and a changed region image acquisition unit that acquires images which correspond to the changed region detected by the detection unit from a first image in which the space represented by the first map is captured and a second image in which the space represented by the second map is captured.

Abstract: An abnormality determination device includes: an analysis unit that analyzes at least a feature amount related to a pattern of a captured image of a manhole cover, the feature amount being included in coded information obtained by coding the captured image; and a determination unit that determines based on an analysis result of the analysis unit whether the manhole cover is abnormal.

Abstract: A position determination apparatus for determining, from a first image that is an image including at least a desired first subject, a position of the desired first subject, includes: a feature amount acquisition unit that acquires a first feature amount representing a predetermined feature of the first image; an estimation unit in which a second feature amount representing the predetermined feature obtained from a second image including a second subject is associated with a selected feature map that is a feature map corresponding to the second subject among a plurality of feature maps that are a set of feature maps that are maps representing features of the second image; an estimated first feature map that is estimated by the estimation unit to be associated with the first feature amount: and a position determination unit that determines the position of the desired first subject using the estimated first feature map.

Abstract: A fading simulator includes a transition time setting means that sets up a predetermined transition time, at the time of switching of a fading setting using a fading parameter, between the fading setting before switching and the fading setting after switching, and a smoothing processing means that smoothly changes a value before the switching to a value after the switching with respect to at least one of a delay parameter, a Doppler effect parameter and a path loss parameter, during the transition time.

Abstract: A fading simulator includes a transition time setting means that sets up a predetermined transition time, at the time of switching of a fading setting using a fading parameter, between the fading setting before switching and the fading setting after switching, and a smoothing processing means that smoothly changes a value before the switching to a value after the switching with respect to at least one of a delay parameter, a Doppler effect parameter and a path loss parameter, during the transition time.