Paper Info
Title
A hybrid unsupervised/supervised model for group activity recognition
Abstract
The new method proposed here recognizes activities performed by a group of users (e.g., attending a meeting, playing sports, and participating in a party) by using sensor data obtained from the users. Note that such group activities (GAs) have characteristics that differ from those of single user activities. For example, the number of users who participate in a GA is different for each activity. The number of meeting participants, for instance, may sometimes be different for each meeting. Also, a user may play different roles (e.g., `moderator' and `presenter' roles) in meetings on different days. We introduce the notion of role into our GA recognition model and try to capture the intrinsic characteristics of GAs with a hybrid unsupervised/supervised approach.
Year
DOI
Venue
2013
10.1145/2493988.2494348
ISWC
Keywords
Field
DocType
different role,different day,intrinsic characteristic,supervised model,ga recognition model,meeting participant,new method,group activity,supervised approach,sensor data,single user activity,group activity recognition,activity recognition
Activity recognition,Computer science,Group activity recognition,Artificial intelligence,Group activity,Machine learning
Conference
Citations 
PageRank 
References 
8
0.65
4
Authors
2
Name
Order
Citations
PageRank
Tomoya Hirano1211.94
Takuya Maekawa232649.93