The purpose of this dissertation is to present our agent-based human tracking framework, and to evaluate the results of our work in light of the previous research in the same field.
Our agent-based approach departs from a process-centric model where the agents are bound to specific processes, and introduces a novel model by which agents are bound to the objects or sub-objects being recognized or tracked. The hierarchical agent-based model allows the system to handle a variety of cases, such as single people or multiple people in front of single or stereo cameras. We employ the job-market model for agents' communication. In this dissertation, we will present several experiments in detail, which demonstrate the effectiveness of the agent-based tracking system.
Per our research, the agents are designed to be autonomous, self-aware entities that are capable of communicating with other agents to perform tracking within agent coalitions. Each agent with high-level abstracted knowledge seeks evidence for its existence from the low-level features (e.g. motion vector fields, color blobs) and its peers (other agents representing body-parts with which it is compatible). The power of the agent-based approach is its flexibility by which the domain information may be encoded within each agent to produce an overall tracking solution. / Ph. D.
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/77135 |
| Date | 12 August 2011 |
| Creators | Fang, Bing |
| Contributors | Computer Science, Quek, Francis K. H., Cao, Yang, Gracanin, Denis, Abbott, A. Lynn, Ehrich, Roger W. |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Language | en_US |
| Detected Language | English |
| Type | Dissertation, Text |
| Format | application/pdf, application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
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