Abstract: An object detection method is provided. The method includes the steps of: acquiring a plurality of frame images; detecting a first bounding box of a first object and a second bounding box of a second object from a first frame image; assigning a first identification value to the first bounding box and a second identification value to the second bounding box; generating a virtual bounding box of the first object in a second frame image; assigning the first identification value to a third bounding box of the first object detected from the second frame image, on the basis of a size of an area where the third bounding box overlaps the virtual bounding box; and changing the second identification value to the first identification value on the basis of a size of an area where the first bounding box overlaps the second bounding box.

Abstract: A method for acquiring visitor information is provided. The method includes the steps of: detecting one or more visitor objects from a video; estimating attribute information of a first visitor using feature data of a first visitor object; acquiring a perspective model of the first visitor on the basis of a travel route of the first visitor object; and acquiring interaction information of the first visitor using the perspective model of the first visitor.

Abstract: An interaction information estimation method is provided. The method includes the steps of: determining, on the basis of a relationship between a product region and a first person detected in a plurality of video frames, whether contact is made between the first person and a product included in the product region, thereby estimating information on an interaction between the first person and the product on the basis of a result of the determination; and validating the estimated information on the interaction.

Abstract: An interaction detection method is provided. The method includes the steps of: acquiring one or more frame images; acquiring pose data of a first object using information on a plurality of feature points detected for the first object from a first frame image; determining occurrence of an interaction of the first object using the pose data of the first object; estimating a region of interest (ROI) of the first object using the information on the plurality of feature points; and acquiring information on a product corresponding to the region of interest of the first object.

Abstract: A method for light-weighting an artificial neural network model, the method comprising is provided. The method includes the steps of: learning, on the basis of a channel length of a 1×1 pruning unit applied in a channel direction to each of a plurality of kernels included in an artificial neural network model, a pruning factor for each of the pruning units and a weight for each of the pruning units; and determining, on the basis of at least one of the learned pruning factors and weights, which of the pruning units is to be removed from the artificial neural network model, wherein the channel length of the pruning unit is shorter than a channel length of at least a part of the plurality of kernels.

Abstract: A method for analyzing a visitor on the basis of a video in an edge computing environment is provided. The method includes the steps of: extracting feature data from a captured video of an offline space; generating detection data on a location and an appearance of an object contained in the captured video from the feature data using an artificial neural network-based detection model; and integrating detection data of a location and an appearance of a target object.

Abstract: An object detection method is provided. The method includes the steps of: acquiring a plurality of frame images; detecting a first bounding box of a first object and a second bounding box of a second object from a first frame image; assigning a first identification value to the first bounding box and a second identification value to the second bounding box; generating a virtual bounding box of the first object in a second frame image; assigning the first identification value to a third bounding box of the first object detected from the second frame image, on the basis of a size of an area where the third bounding box overlaps the virtual bounding box; and changing the second identification value to the first identification value on the basis of a size of an area where the first bounding box overlaps the second bounding box.

Abstract: An interaction detection method is provided. The method includes the steps of: acquiring one or more frame images; acquiring pose data of a first object using information on a plurality of feature points detected for the first object from a first frame image; determining occurrence of an interaction of the first object using the pose data of the first object; estimating a region of interest (ROI) of the first object using the information on the plurality of feature points; and acquiring information on a product corresponding to the region of interest of the first object.

Abstract: A method for acquiring visitor information is provided. The method includes the steps of: detecting one or more visitor objects from a video; estimating attribute information of a first visitor using feature data of a first visitor object; acquiring a perspective model of the first visitor on the basis of a travel route of the first visitor object; and acquiring interaction information of the first visitor using the perspective model of the first visitor.

Abstract: An interaction information estimation method is provided. The method includes the steps of: determining, on the basis of a relationship between a product region and a first person detected in a plurality of video frames, whether contact is made between the first person and a product included in the product region thereby estimating information on an interaction information between the first person and the product on the basis of a result of the determination; and validating the estimated information on the interaction.