<p>A new, computationally efficient windowing methodology for motion tracking is described. The proposed approach is well suited to real-time focus-of-attention applications in which regions-of-interest, or windows, are used to reduce image data rates. Applications include robot guidance, where high speed image processing is required for real-time position control in operations such as fixtureless assembly for flexible manufacturing. A hierarchy of windowing functions which includes motion detection and target detection and tracking has been developed. This has resulted in a new algorithm for corner detection in image windows, as well as a proposal for measuring the information content of an image based on corner location accuracy. The techniques have been experimentally verified with the implementation of a vision system based on a high speed digital camera, a custom-built video interface board, and a network of digital signal processors. Dynamically positioned at video frame rates, windows within the camera field-of-view are made cooperative by exchanging information among their corresponding processors to allow real-time adaptation to visual motion. A cooperative windowing scheme using two networked target tracking windows is demonstrated. Motion tracking is based on the best-case output of the simultaneous application of a feature-based algorithm applied in the first window and a model-based algorithm running in the second. The experimental results demonstrate the advantages of motion tracking using this cooperative windows approach.</p> / Doctor of Philosophy (PhD)
| Identifer | oai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/8132 |
| Date | 04 1900 |
| Creators | Nassif, Samer Chaker |
| Contributors | Capson, David, Elbestawi, M.A., Electrical and Computer Engineering |
| Source Sets | McMaster University |
| Detected Language | English |
| Type | thesis |
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