Abstract: Example implementations include a method, apparatus and computer-readable medium for generating a visual model of a uniform, comprising detecting a plurality of persons in one or more images. The implementations further include generating a sub-image depicting the respective person from the one or more images for each respective person of the plurality of persons. Additionally, the implementations further include identifying one or more articles of clothing worn by the respective person, executing at least one transformation that adjusts pixels of the sub-image such that the one or more articles of clothing depicted in the sub-image fit in a common template, calculating variance values between a plurality of transformed sub-images comprising the sub-image transformed by the at least one transformation and other sub-images generated for other persons in the plurality of persons and transformed by the at least one transformation, and generating a virtual model based on the variance values.

Abstract: Example implementations include a method, apparatus and computer-readable medium for computer vision detection of dwell time, comprising receiving a plurality of indications of persons entering an environment over a period of time. The implementations further include adding, into a first-in-first-out (FIFO) queue, a respective identifier of a respective person entering the environment and an entry time for each of the plurality of indications, removing, from the FIFO queue, the respective identifier and the entry time of the respective person in response to an indication of an exit of the respective person from the environment at an exit time, calculating an estimated dwell time of the respective person based on a difference in the entry time and the exit time, and generating an alert based on calculating an average dwell time of the persons entering the environment over the period of time based on each estimated dwell time.

Abstract: Disclosed herein are apparatuses and methods for iteratively mapping a layout of an environment. The implementations include receiving a visual stream from a camera installed in the environment, wherein the visual stream depicts a view of the environment, and wherein positional parameters of the camera and dimensions of the environment are set to arbitrary values. The implementations include monitoring a plurality of persons in the visual stream. For each person in the plurality of persons, the implementations further includes identifying a respective path that the person moves along in the view, updating the dimensions of the environment captured in the view, based on an estimated height of the person and movement speed along the respective path, and updating the positional parameters of the camera based on the updated dimensions of the environment. The implementations further includes mapping a layout of the environment captured in the view of the camera.

Abstract: Example implementations include a method, apparatus and computer-readable medium for computer vision detection of dwell time, comprising receiving a plurality of indications of persons entering an environment over a period of time. The implementations further include adding, into a first-in-first-out (FIFO) queue, a respective identifier of a respective person entering the environment and an entry time for each of the plurality of indications, removing, from the FIFO queue, the respective identifier and the entry time of the respective person in response to an indication of an exit of the respective person from the environment at an exit time, calculating an estimated dwell time of the respective person based on a difference in the entry time and the exit time, and generating an alert based on calculating an average dwell time of the persons entering the environment over the period of time based on each estimated dwell time.

Abstract: Example implementations include a method, apparatus and computer-readable medium for generating a visual model of a uniform, comprising detecting a plurality of persons in one or more images. The implementations further include generating a sub-image depicting the respective person from the one or more images for each respective person of the plurality of persons. Additionally, the implementations further include identifying one or more articles of clothing worn by the respective person, executing at least one transformation that adjusts pixels of the sub-image such that the one or more articles of clothing depicted in the sub-image fit in a common template, calculating variance values between a plurality of transformed sub-images comprising the sub-image transformed by the at least one transformation and other sub-images generated for other persons in the plurality of persons and transformed by the at least one transformation, and generating a virtual model based on the variance values.