Abstract: A light detector is configured such that a light receiving portion having APDs and a peripheral portion are provided on a first principal surface of a p-type semiconductor substrate, and further includes a back electrode provided on a second principal surface of the semiconductor substrate and a p-type first separation portion provided between the light receiving portion and the peripheral portion. The APD has, on a first principal surface side, an n-type region and a p-epitaxial layer contacting the n-type region in a Z-direction. The peripheral portion has an n-type MISFET provided at a p-well and an n-well provided to surround entire side and bottom portions of the p-well.

Abstract: A shape similarity computation unit (2021) computes, as a shape similarity, a similarity in shape between a learning movement path curve which is a movement path curve obtained through learning and an observation movement path curve which is a movement path curve obtained through observation. A position similarity computation unit (2022) computes, as a position similarity, a similarity in position between the learning movement path curve and the observation movement path curve when the learning movement path curve and the observation movement path curve are placed in a same coordinate space. A conformity computation unit (203) computes a conformity between the learning movement path curve and the observation movement path curve, using the shape similarity and the position similarity.

Abstract: A movement route estimation device (50) includes an object search unit (504) and a movement route estimation unit (505). The object search unit (504) searches for, as a search feature value, each feature value of two or more feature values from among a plurality of object feature values, based on a similarity between a feature value corresponding to a movable object, which is an object that has moved in a target space in a target period, and a target feature value.

Abstract: A basic-action-model acquisition unit (103) acquires a basic-action model which has been generated by analyzing a state of each of a plurality of parts of a movable object when the movable object performs a basic action, and which is a model for recognizing the basic action, for each of a plurality of the basic actions. An advanced-action-model generation unit (104) combines two or more basic-action models among a plurality of basic-action models, and generates an advanced-action model which is a model for recognizing an advanced action which is an action more complex than the basic action.

Abstract: A first estimation unit (23) estimates, on the basis of sensor data acquired from a sensor (42) allocated to a first position in a target space, a first congestion degree being a congestion degree about the first position. A second estimation unit (26) estimates a second congestion degree being a congestion degree about a second position, on the basis of the first congestion degree, the second position being a position on a travel route of a traveling object in the target space and being different from the first position. A third estimation unit (27) estimates a third congestion degree being a congestion degree about a third position which is neither the first position nor the second position in the target space, on the basis of the first congestion degree and the second congestion degree.