Omni-directional (O-D) infrared (IR) vision is an effective capability for mobile systems in robotics, due to its advantages: illumination invariance, wide field-of-view, ease of identifying heat-emitting objects, and long term tracking without interruption. Unfortunately, O-D IR sensors have low resolution, low frame rates, high cost, sensor noise, and an increase in tracking time. In order to overcome these disadvantages, we propose an autonomous system application in indoor scenarios including 1) Dynamic 3D Reconstruction (D3DR) of the target view in real time images, 2) Human Behavior-based Target Tracking from O-D thermal images, 3) Thermal Multisensor Fusion (TMF), and 4) Visual Perception for Social Cognition from the motion behavior of the human target.
| Identifer | oai:union.ndltd.org:vcu.edu/oai:scholarscompass.vcu.edu:etd-6113 |
| Date | 01 January 2017 |
| Creators | Benli, Emrah |
| Publisher | VCU Scholars Compass |
| Source Sets | Virginia Commonwealth University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Theses and Dissertations |
| Rights | © The Author |
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