Augmented Reality (AR) has become a popular area in computer Science where research studies and technological innovations are extensive. Research in AR first began in the early 1990s and thenceforth, a number of dierent tracking algorithms and methods have been developed. Tracking systems have a critical importance for AR and marker based vision tracking systems became the mostly used tracking systems due to their low cost and ease of use. Basically, marker systems consist of special patterns that are placed in the environment and detected by simple cameras. In this thesis, we propose a new marker system based on topological tracking where markers are detected and identified using their topology trees. In our proposed marker system, we create topology trees of markers as region adjacency graphs that are obtained from binary images of the markers. Similarly, camera frames are also converted into binary images and corresponding topology trees are created. We used left heavy
depth sequences as the canonical convention for the topology trees. For marker tracking, we used a simplified version of subgraph isomorphism algorithm that searches marker topology
trees in a frame topology tree. Finally, we tested our proposed system for performance in using spatially distinct marker parts / occlusion resolving / detection rate with respect to marker
size, camera-marker angle, false positive marker detection / performance with respect marker library size. Our system achieved 90% marker detection success with 50 pixels marker size and an average of 1.1 false positive marker detection in ten dierent test videos. We made all tests in comparison with the widely used ARToolkit library. Our system surpasses the
ARToolkit library for all tests performed. In addition, our system enables spatially distinct placement of marker parts and permits occlusion unless the topology of the marker is not
corrupted, but the ARToolkit library does not have these features.
| Identifer | oai:union.ndltd.org:METU/oai:etd.lib.metu.edu.tr:http://etd.lib.metu.edu.tr/upload/12611623/index.pdf |
| Date | 01 March 2010 |
| Creators | Ercan, Munir |
| Contributors | Can, Tolga |
| Publisher | METU |
| Source Sets | Middle East Technical Univ. |
| Language | English |
| Detected Language | English |
| Type | M.S. Thesis |
| Format | text/pdf |
| Rights | To liberate the content for public access |
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