Motion based situation recognition in group meetings

Julia Moehrmann; Xin Wang; Gunther Heidemann

doi:10.1117/12.838963

28 January 2010 Motion based situation recognition in group meetings

Julia Moehrmann, Xin Wang, Gunther Heidemann

Proceedings Volume 7538, Image Processing: Machine Vision Applications III; 75380N (2010) https://doi.org/10.1117/12.838963
Event: IS&T/SPIE Electronic Imaging, 2010, San Jose, California, United States

Abstract

We present an unobtrusive vision based system for the recognition of situations in group meetings. The system uses a three-stage architecture, consisting of one video processing stage and two classification stages. The video processing stage detects motion in the videos and extracts up to 12 features from this data. The classification stage uses Hidden Markov Models to first identify the activity of every participant in the meeting and afterwards recognize the situation as a whole. The feature extraction uses position information of both hands and the face to extract motion features like speed, acceleration and motion frequency, as well as distance based features. We investigate the discriminative ability of these features and their applicability to the task of interaction recognition. A two-stage Hidden Markov Model classifier is applied to perform the recognition task. The developed system classifies the situation in 94% of all frames in our video test set correctly, where 3% of the test data is misclassified due to contradictory behavior of the participants. The results show that unimodal data can be sufficient to recognize complex situations.

Citation Download Citation

Julia Moehrmann, Xin Wang, and Gunther Heidemann "Motion based situation recognition in group meetings", Proc. SPIE 7538, Image Processing: Machine Vision Applications III, 75380N (28 January 2010); https://doi.org/10.1117/12.838963

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available