Movement determination method, movement determination device and computer-readable storage medium
AssigneeBomdic Inc.
InventorsLeong Kian Tee, Haoyi Chih, En-Tzu Wang
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Abstract
The disclosure provides a movement determination method, a movement determination device, and a computer-readable storage medium. The method includes the following. In response to determining that a user has presented an initial movement corresponding to a to-be-detected movement, an anchor joint point among multiple joint points of the user is decided based on the to-be-detected movement. A movable range of each of the anchor joint points is decided. In response to determining that each of the anchor joint points leaves the corresponding movable range, it is determined that the user has stopped performing the to-be-detected movement.
Claims19
A movement determination method, suitable for a movement determination device, comprising:
- obtaining a plurality of images of a user, and feeding the images of the user into a machine learning model, wherein the machine learning model determines whether the user has presented an initial movement corresponding to a to-be-detected movement according to the images of the user;
- in response to determining that the user has presented the initial movement corresponding to the to-be-detected movement, deciding at least one anchor joint point among a plurality of joint points of the user based on the to-be-detected movement;
- deciding a movable range of each of the anchor joint points;
- and
- in response to determining that each of the anchor joint points leaves the corresponding movable range, determining that the user has stopped performing the to-be-detected movement.
A movement determination device, comprising:
- a non-transitory storage circuit storing a program code;
- and
- a processor coupled to the non-transitory storage circuit and accessing the program code to perform:
- obtaining a plurality of images of a user, and feeding the images of the user into a machine learning model, wherein the machine learning model determines whether the user has presented an initial movement corresponding to a to-be-detected movement according to the images of the user;
- in response to determining that the user has presented the initial movement corresponding to the to-be-detected movement, deciding at least one anchor joint point among a plurality of joint points of the user based on the to-be-detected movement;
- deciding a movable range of each of the anchor joint points;
- and
- in response to determining that each of the anchor joint points leaves the corresponding movable range, determining that the user has stopped performing the to-be-detected movement.
A non-transitory computer-readable storage medium, wherein the computer-readable storage medium records an executable computer program, and the executable computer program is loaded by a movement determination device to perform:
- obtaining a plurality of images of a user, and feeding the images of the user into a machine learning model, wherein the machine learning model determines whether the user has presented an initial movement corresponding to a to-be-detected movement according to the images of the user;
- in response to determining that the user has presented the initial movement corresponding to the to-be-detected movement, deciding at least one anchor joint point among a plurality of joint points of the user based on the to-be-detected movement;
- deciding a movable range of each of the anchor joint points;
- and
- in response to determining that each of the anchor joint points leaves the corresponding movable range, determining that the user has stopped performing the to-be-detected movement.
Dependencies are inferred from the claim text.