FITNESS DEVICE-BASED SIMULATOR AND SIMULATION METHOD USING THE SAME

摘要

A fitness device-based simulator and a simulation method using the simulator. The fitness device-based simulator includes a feature point extraction unit for acquiring action-sensing information of a user who is located on a fitness device, and extracting feature points for a body skeletal structure of the user based on the action-sensing information, a feature point cluster generation unit for generating multiple feature point clusters by clustering two or more of the feature points, and setting respective cluster symbols for multiple feature point clusters, an exercise pattern information accumulation unit for generating and storing information about a state transition between the multiple feature point clusters of the user, and an exercise state prediction unit for predicting a subsequent exercise state of the user by predicting a feature point cluster subsequent to a feature point cluster currently being generated for the user, based on state transition information.

主权项

1. A fitness device-based simulator, comprising:
a feature point extraction unit for acquiring action-sensing information of a user who is located on a fitness device from one or more camera sensors, and extracting feature points for a body skeletal structure of the user per unit time based on the action-sensing information; a feature point cluster generation unit for generating multiple feature point clusters by clustering two or more of the feature points extracted by the feature point extraction unit within a preset period of time, and setting respective cluster symbols for the multiple feature point clusters; an exercise pattern information accumulation unit for generating and storing information about a state transition between the multiple feature point clusters of the user using the cluster symbols of the respective feature point clusters set by the feature point cluster generation unit; and an exercise state prediction unit for predicting a subsequent exercise state of the user by predicting a feature point cluster subsequent to a feature point cluster currently being generated for the user, based on the information about state transition between the multiple feature point clusters for the user, which is previously stored in the exercise pattern information accumulation unit.