ROAD SURVEILLANCE SYSTEM, ROAD SURVEILLANCE METHOD, AND NON-TRANSITORY STORAGE MEDIUM

    公开(公告)号:US20240105053A1

    公开(公告)日:2024-03-28

    申请号:US18237119

    申请日:2023-08-23

    Abstract: To improve efficiency of road surveillance, a road surveillance system includes a detection unit 122 and a processing unit 134. The detection unit 122 detects a road state being a state of an object on a road by processing an image in which the road is captured. The processing unit 134 performs, when the road state satisfies a first criterion, any of notification processing of making a notification of the road state that satisfies the first criterion according to notification setting related to the notification, and change-related processing related to a change in the notification setting, based on whether a second criterion is satisfied. The second criterion is a criterion related to a determination result of whether the road state satisfies the first criterion.

    ROAD SURVEILLANCE SYSTEM, ROAD SURVEILLANCE METHOD, AND NON-TRANSITORY STORAGE MEDIUM

    公开(公告)号:US20240104931A1

    公开(公告)日:2024-03-28

    申请号:US18237129

    申请日:2023-08-23

    CPC classification number: G06V20/54 G06V20/46 G06V2201/07 G06V2201/08

    Abstract: A road surveillance system includes a video acquisition unit, a target determination unit, and a display control unit. The video acquisition unit acquires a video that captures a road. The target determination unit determines, based on a result of comparison between at least one frame image constituting the video and a reference image, and a first criterion, whether the at least one frame image is an analysis target. The display control unit causes a display unit to display information based on a result of the determination. The display control unit includes a first control unit and a second control unit. The first control unit causes the display unit to display an analysis result of at least one frame image being determined to be an analysis target. The second control unit causes the display unit to display detection information indicating that a frame image not being an analysis target is detected.

    Learning device, learning method, and storage medium

    公开(公告)号:US11270163B2

    公开(公告)日:2022-03-08

    申请号:US16772035

    申请日:2017-12-14

    Abstract: A learning device comprises: an acquisition unit that acquires a first feature amount derived by an encoder from data with an identification object recorded therein, the encoder being configured so as to derive, from data with the identical object in various forms recorded therein, feature amounts which are mutually convertible by a conversion using a conversion parameter that takes a value according to the difference in the forms; a conversion unit that generates a second feature amount by performing a conversion on the first feature amount using the conversion parameter value; and a parameter updating unit that updates the value of a sorting parameter used in sorting by a sorting means, which is configured to sort second feature amounts as input, such that if the second feature amount has been input, the sorting means outputs a result indicating, as a sorting destination, a class associated with the identification object.

    Learning device, learning method, and storage medium

    公开(公告)号:US11526691B2

    公开(公告)日:2022-12-13

    申请号:US16772057

    申请日:2017-12-14

    Abstract: Provided is a learning device that can generate a feature deriving device capable of deriving, for an identical object, feature amounts which respectively express a feature of the object in different forms and which are mutually related. This learning device comprises: an acquisition unit that acquires first data and second data, with different forms of the object recorded therein; an encoder that derives a first feature amount from the first data; a conversion unit that converts the first feature amount to a second feature amount; a decoder that generates third data from the second feature amount; and a parameter updating unit that updates, on the basis of a comparison between the second data and the third data, the value of a parameter used in the derivation of the first feature amount, and the value of a parameter used in the generation of the third data.

    Image processing device, image processing method and storage medium

    公开(公告)号:US11227367B2

    公开(公告)日:2022-01-18

    申请号:US16644560

    申请日:2017-09-08

    Abstract: An image processing device which is capable of accurately detect pixels covered by cloud shadows and remove effects of the cloud shadows in an images are provided. The device includes: a cloud transmittance calculation unit that calculates transmittance of the one or more clouds in an input image, for each pixel; a cloud height estimation unit that determines estimation of a height from the ground to each cloud in the input image to detect position of corresponding one or more shadows; an attenuation factor estimation unit that calculates attenuation factors for the direct sun irradiance by applying an averaging filter to the cloud transmittance calculated; and a shadow removal unit that corrects pixels affected by the one or more shadows, based on a physical model of a cloud shadow formation by employing the attenuation factors calculated and the position, and outputs an image which includes the pixels corrected.

    Identification device, identification method, and storage medium

    公开(公告)号:US11176420B2

    公开(公告)日:2021-11-16

    申请号:US16769135

    申请日:2017-12-14

    Abstract: An identification device according to one embodiment comprises: an acquisition unit that uses an encoder configured to derive, from data in which a single subject under different conditions has been recorded, feature values as a first feature value derived from data in which a subject to be identified has been recorded; a conversion unit that generates a second feature value by carrying out conversion using the conversion parameter on the first feature value; a discrete classification unit that carries out discrete classification on each of a plurality of third feature values including the second feature value and generates a plurality of discrete classification results indicating the results of the classification; a result derivation unit that derives, on the basis of the plurality of discrete classification results, identification result information; and an output unit that outputs the identification result information.

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