Advanced New Technologies Co., Ltd.

Zhangjun Hou

Xiaobo Zhang

Xudong Yang

Xiaodong Zeng

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.

Abnormality detection method, apparatus, and device for unmanned checkout

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.

Growing community of inventors

Hangzhou, China

Zhangjun Hou