Abstract: Embodiments of the present specification provide abnormality detection methods, apparatuses, and devices for unmanned checkout. In an embodiment, a method comprising: obtaining, by a depth camera in a detection area of a photographing area for unmanned checkout, image data that comprises a depth image and a corresponding RGB image; detecting, based on the image data, one or more customers that enter the detection area for unmanned checkout using one or more of headcount detection to detect a quantity of the one or more customers or gesture detection to detect one or more gestures of the one or more customers; and in response to determining that the quantity of the one or more customers is greater than a predetermined threshold or the one or more gestures comprise an abnormal gesture, notifying a central control system to stop the unmanned checkout and trigger an alarm.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for on-shelf merchandise detection are provided. One of the methods includes: obtaining a plurality of depth images associated with a shelf from a first camera; obtaining a plurality of images from one or more second cameras associated with each of a plurality of tiers of the shelf; detecting motions of a user's hand comprising reaching into and moving away from the shelf; determining one of the tiers of the shelf associated with the detected motions, a first point of time associated with reaching into the shelf, and a second point of time associated with moving away from the shelf; identifying a first image captured before the first point in time and a second image captured after the second point in time; and comparing the first image and the second image to determine one or more changes to merchandise.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for on-shelf merchandise detection are provided. One of the methods includes: obtaining a plurality of depth images associated with a shelf from a first camera; obtaining a plurality of images from one or more second cameras associated with each of a plurality of tiers of the shelf; detecting motions of a user's hand comprising reaching into and moving away from the shelf; determining one of the tiers of the shelf associated with the detected motions, a first point of time associated with reaching into the shelf, and a second point of time associated with moving away from the shelf; identifying a first image captured before the first point in time and a second image captured after the second point in time; and comparing the first image and the second image to determine one or more changes to merchandise.

Abstract: Embodiments of the present specification provide product information query methods and systems. In an embodiment, a method comprising detecting, by a distance sensor, a moving object that enters a predetermined detection range, wherein the moving object comprises a product; sending, by the distance sensor, a notification that that notifies a computer of the one or more computers to enable a query of the product; photographing, by a photographing device, an image of the product; obtaining, by a computer, the image from the photographing device; extracting, by the computer and from the image, image features of the product; performing, by the computer, the query to obtain product information based on the image features; and displaying, by a display, the product information.

Abstract: Embodiments of the present specification provide abnormality detection methods, apparatuses, and devices for unmanned checkout. In an embodiment, a method comprising: obtaining, by a depth camera in a detection area of a photographing area for unmanned checkout, image data that comprises a depth image and a corresponding RGB image; detecting, based on the image data, one or more customers that enter the detection area for unmanned checkout using one or more of headcount detection to detect a quantity of the one or more customers or gesture detection to detect one or more gestures of the one or more customers; and in response to determining that the quantity of the one or more customers is greater than a predetermined threshold or the one or more gestures comprise an abnormal gesture, notifying a central control system to stop the unmanned checkout and trigger an alarm.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for on-shelf merchandise detection are provided. One of the methods includes: obtaining a plurality of depth images associated with a shelf from a first camera; obtaining a plurality of images from one or more second cameras associated with each of a plurality of tiers of the shelf; detecting motions of a user's hand comprising reaching into and moving away from the shelf; determining one of the tiers of the shelf associated with the detected motions, a first point of time associated with reaching into the shelf, and a second point of time associated with moving away from the shelf; identifying a first image captured before the first point in time and a second image captured after the second point in time; and comparing the first image and the second image to determine one or more changes to merchandise.