Abstract: In an attention ability inspection method, at least one of a central task of unsteadily changing a central graphic at a predetermined speed and a peripheral task of displaying a peripheral graphic in a peripheral region of a display area is randomly presented in a state in which the central graphic is displayed in a central region of the display area of a display, time from presentation of the central task or the peripheral task to reception of a predetermined operation from a subject that has recognized the presentation is measured as reaction time, and an attention ability of the subject is evaluated based on the reaction time.

Abstract: According to one embodiment, an elevator passenger detection system comprises an image capturing unit, a detection area setting unit, and a detection processing unit. The image capturing unit captures an image in a predetermined range including a vicinity of a doorway at which a door is opened or closed, from an inside of a car. The detection area setting unit sets a detection area on a front return panel provided on at least one of sides of a doorway of the car, on the captured image obtained by the image capturing unit. The detection processing unit detects presence of a passenger or an object, based on the image in the detection area set by the detection area setting unit.

Abstract: An attention ability test device includes a display having a display area, an input device for receiving an operation performed by an examinee, and a test controller. While displaying a central image in the central area of the display area and displaying one or more peripheral images in the peripheral area of the display area, the test controller generates at random at least one of a center task of changing the central image and a periphery task of changing the peripheral image, and measures, as a reaction time, the period of time from generation of the center task or the periphery task to execution of a predetermined operation performed by the examinee having recognized the generation, and evaluates the attention ability of the examinee, based on the reaction time.

Abstract: In an attention ability inspection method, at least one of a central task of unsteadily changing a central graphic at a predetermined speed and a peripheral task of displaying a peripheral graphic in a peripheral region of a display area is randomly presented in a state in which the central graphic is displayed in a central region of the display area of a display, time from presentation of the central task or the peripheral task to reception of a predetermined operation from a subject that has recognized the presentation is measured as reaction time, and an attention ability of the subject is evaluated based on the reaction time.

Abstract: According to one embodiment, a user detection system includes a camera, a boundary detector, a user detector and a controller. The camera is installed in a peripheral region of a door, and captures a running region when opening or closing the door and a region near the door. The boundary detector detects a boundary between a first structure and a second structure in the region near the door based on an image captured by the camera. The user detector detects whether there is a user in the running region based on a result detected by the boundary detector. The controller controls an open/close operation of the door based on a result detected by the user detector.

Abstract: According to one embodiment, an elevator passenger detection system comprises an image capturing unit, a detection area setting unit, and a detection processing unit. The image capturing unit captures an image in a predetermined range including a vicinity of a doorway at which a door is opened or closed, from an inside of a car. The detection area setting unit sets a detection area on a front return panel provided on at least one of sides of a doorway of the car, on the captured image obtained by the image capturing unit. The detection processing unit detects presence of a passenger or an object, based on the image in the detection area set by the detection area setting unit.

Abstract: According to one embodiment, an image detection system includes an imaging apparatus, an edge extraction unit, a specific-edge extraction unit, a candidate area extraction unit, and a to-be-detected area determination unit. The edge extraction unit extracts edges each representing a boundary line between areas with different features. The specific-edge extraction unit extracts specific edges including at least remaining edges present in background image and input image. The candidate area extraction unit extracts candidate areas for a preset area to be detected. The to-be-detected area determination unit determines the area to be detected from candidate areas extracted.

Abstract: According to one embodiment, a user detection system includes a camera, a boundary detector, a user detector and a controller. The camera is installed in a peripheral region of a door, and captures a running region when opening or closing the door and a region near the door. The boundary detector detects a boundary between a first structure and a second structure in the region near the door based on an image captured by the camera. The user detector detects whether there is a user in the running region based on a result detected by the boundary detector. The controller controls an open/close operation of the door based on a result detected by the user detector.

Abstract: According to one embodiment, an image detection system includes an imaging apparatus, an edge extraction unit, a specific-edge extraction unit, a candidate area extraction unit, and a to-be-detected area determination unit. The edge extraction unit extracts edges each representing a boundary line between areas with different features. The specific-edge extraction unit extracts specific edges including at least remaining edges present in background image and input image. The candidate area extraction unit extracts candidate areas for a preset area to be detected. The to-be-detected area determination unit determines the area to be detected from candidate areas extracted.

Abstract: According to one embodiment, an elevator system includes a camera, a passenger detection module and a controller. The camera is capable of imaging a particular range in a direction from a vicinity of a door of a car to a hall when the car arrives at the hall. The passenger detection module detects presence or absence of a passenger who intends to get into the car by focusing on movement of a movable body within a specific area by using a plurality of time-series continuous images which are captured by the camera. The controller controls an opening/closing operation of the door based on a detection result of the passenger detection module. A width of the area is being set greater than at least a width of the door.

Abstract: According to an embodiment, an information processing device includes an input, a first storage, an acquirer, and a second storage. The input receives image data from an imager that captures, from a vehicle, an image of surroundings of the vehicle. The first storage stores, in correlation with each other, identification information for identifying a road structure contained in the image data for guiding the vehicle, and category information indicating a category of the road structure. The acquirer acquires location information representing a spot at which the vehicle is traveling. The second storage stores, in correlation with one another, the image data from which the road structure is detected based on the identification information stored in the first storage, the category information, and the location information indicating a spot at which the vehicle is traveling at the time of capturing the image data containing the road structure.

Abstract: An embodiment of a vehicle monitoring apparatus has a determiner and a reader. The determiner determines whether or not a specific site of a vehicle exists at least in an area of an image, the image imaged by an imager, the area being one of multiple areas into which the image is divided by dividing line that are substantially orthogonal to a direction of travel of the vehicle. The reader reads information on a license plate mounted to the vehicle from the area in case that the determiner determines the specific site of the vehicle is determined to exist in the area.

Abstract: According to one embodiment, an elevator system includes a camera, a passenger detection module and a controller. The camera is capable of imaging a particular range in a direction from a vicinity of a door of a car to a hall when the car arrives at the hall. The passenger detection module detects presence or absence of a passenger who intends to get into the car by focusing on movement of a movable body within a specific area by using a plurality of time-series continuous images which are captured by the camera. The controller controls an opening/closing operation of the door based on a detection result of the passenger detection module. A width of the area is being set greater than at least a width of the door.

Abstract: An image processing system of an embodiment includes a first analyzer, an image processor, and a first scaler. The first analyzer is configured to analyze image data to generate an analysis result. The image processor is configured to perform image processing of the image data in accordance with the analysis result, to generate processed image data. The image processor includes a first image processor and a second image processor. The second image processor is configured to receive an output from the first image processor. The first scaler configured to determine whether the analysis result is usable with respect to the image data to be used by the second image processor after the first image processor performs the image processing, and to scale the analysis result to be used by the second image processor when the analysis result is not usable with respect to the image data to be used by the second image processor.

Abstract: A parked vehicle detection device includes a vehicle detector, a host-vehicle position detector, a position calculator, a vehicle information storage, and a parked vehicle determiner. The vehicle detector detects another vehicle included in an image of at least a front of a host vehicle, the image captured by an imaging device mounted on the host vehicle. The host-vehicle position detector detects a position of the host vehicle. The position calculator calculates a position of the detected another vehicle based on the detected position of the host vehicle. The vehicle information storage stores therein information on the another vehicle. The information includes the calculated position. The parked vehicle determiner determines whether the another vehicle is a high possible parked vehicle based on the information on the another vehicle.

Abstract: An embodiment of a vehicle monitoring apparatus has a determiner and a reader. The determiner determines whether or not a specific site of a vehicle exists at least in an area of an image, the image imaged by an imager, the area being one of multiple areas into which the image is divided by dividing line that are substantially orthogonal to a direction of travel of the vehicle. The reader reads information on a license plate mounted to the vehicle from the area in case that the determiner determines the specific site of the vehicle is determined to exist in the area.

Abstract: A disclosure describes a learning image collection apparatus includes an acquisition unit, an extraction unit, a calculation unit, and a selection unit. The acquisition unit acquires an image including a target object. The extraction unit extracts, from the image, a plurality of candidate areas being candidates for the target object. The calculation unit calculates one of a first degree of similarity, a second degree of similarity, and a third degree of similarity, the first degree of similarity being a degree of similarity between one of the candidate areas and a predetermined area, the second degree of similarity being a degree of similarity between a size of the target object and a predetermined size, the third degree of similarity being a degree of similarity between the plurality of candidate areas. The selection unit selects one of the candidate areas as a target object area including the target object.

Abstract: A disclosure describes a learning image collection apparatus includes an acquisition unit, an extraction unit, a calculation unit, and a selection unit. The acquisition unit acquires an image including a target object. The extraction unit extracts, from the image, a plurality of candidate areas being candidates for the target object. The calculation unit calculates one of a first degree of similarity, a second degree of similarity, and a third degree of similarity, the first degree of similarity being a degree of similarity between one of the candidate areas and a predetermined area, the second degree of similarity being a degree of similarity between a size of the target object and a predetermined size, the third degree of similarity being a degree of similarity between the plurality of candidate areas. The selection unit selects one of the candidate areas as a target object area including the target object.

Abstract: A first acquisition unit is configured to acquire the image including a plurality of frames. A first extraction unit is configured to extract a plurality of persons from the frames, and to extract a plurality of first attributes from each of the persons. The first attributes feature each person. A second extraction unit is configured to extract a plurality of second attributes from a first person indicated by a user. The second attributes feature the first person. A retrieval unit is configured to retrieve information about a person similar to the first person from the persons, based on at least one of the second attributes as a retrieval condition. An addition unit is configured to, when at least one of the first attributes of a retrieved person by the retrieval unit is different from the second attributes, add the at least one of the first attributes to the retrieval condition.

Abstract: A feature extraction apparatus includes a pixel feature calculator configured to calculate a plurality of pixel features for each of pixels included in a plurality of pieces of image data; a co-occurrence frequency calculator configured to calculate co-occurrence frequencies of the pixel features by comparing the pixel features among corresponding pixels in the pieces of image data; and a co-occurrence frequency output unit configured to output the co-occurrence frequencies.