On Supervised Human Activity Analysis for Structured Environments


Arbab-Zavar, Banafshe, Bouchrika, Imed, Carter, John and Nixon, Mark (2010) On Supervised Human Activity Analysis for Structured Environments. At 6th International Symposium on Visual Computing (ISVC10), Las Vegas, Nevada , USA, Nov - Dec 2010.

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Description/Abstract

We consider the problem of developing an automated visual solution for detecting human activities within industrial environments. This has been performed using an overhead view. This view was chosen over more conventional oblique views as it does not suffer from occlusion, but still retains powerful cues about the activity of individuals. A simple blob tracker has been used to track the most significant moving parts i.e. human beings. The output of the tracking stage was manually labelled into 4 distinct categories: walking; carrying; handling and standing still which are taken together from the basic building blocks of a higher work flow description. These were used to train a decision tree using one subset of the data. A separate training set is used to learn the patterns in the activity sequences by Hidden Markov Models (HMM). On independent testing, the HMM models are applied to analyse and modify the sequence of activities predicted by the decision tree.

Item Type: Conference or Workshop Item (Poster)
Additional Information: Event Dates: November - December, 2010
Divisions: Faculty of Physical Sciences and Engineering > Electronics and Computer Science > Comms, Signal Processing & Control
ePrint ID: 271757
Date Deposited: 07 Dec 2010 16:41
Last Modified: 27 Mar 2014 20:17
Further Information:Google Scholar
ISI Citation Count:0
URI: http://eprints.soton.ac.uk/id/eprint/271757

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