Year: 2019
Type: dissertation
Abstract: This work gives a method which can use both motion and shape information for drinking action detection. Drinking action is differ from the other gestures. A complete drinking action duration could be divided into 3 different stages. Motion-based features and shape-based features are complement with each other in each stage. By using this feature, we have defined a fusion strategy that can use both the advantage of the strength of each part at a different stage.
Author: Xiang Teng
Language: English
Subfield: Human-Computer Interaction
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2966238152