Title :
Duo: a wearable system that learns about everyday objects and actions
Author :
Kemp, Charles C.
Author_Institution :
CSAIL, MIT, Cambridge, MA, USA
fDate :
31 Oct.-3 Nov. 2004
Abstract :
Duo is a wearable system designed to learn about everyday actions and the objects to which they are applied. Duo uses first person video and kinematic sensing of the head, torso, and dominant arm. Duo fundamentally relies on general methods for segmenting both kinematic and visual data into meaningful units. We describe methods for segmenting the wearer´s arm, the objects with which the wearer interacts, and the actions the wearer applies to these objects. Both real-time interactive methods and offline annotation tools are used to help Duo create meaningful segmentations from which to learn.
Keywords :
image segmentation; intelligent robots; manipulator kinematics; mobile robots; kinematic sensing; offline annotation tools; real-time interactive method; visual data segmentation; wearable system; Biomedical monitoring; Humans; Kinematics; Learning systems; Light emitting diodes; Magnetic heads; Matched filters; Real time systems; Refrigeration; Torso;
Conference_Titel :
Wearable Computers, 2004. ISWC 2004. Eighth International Symposium on
Print_ISBN :
0-7695-2186-X
DOI :
10.1109/ISWC.2004.16