Tracking image features using a parallel computational model

Timothy J. Ellis; Majid Mirmehdi; Geoff R. Dowling

doi:10.1117/12.58571

1 March 1992 Tracking image features using a parallel computational model

Timothy J. Ellis, Majid Mirmehdi, Geoff R. Dowling

Proceedings Volume 1708, Applications of Artificial Intelligence X: Machine Vision and Robotics; (1992) https://doi.org/10.1117/12.58571
Event: Aerospace Sensing, 1992, Orlando, FL, United States

Abstract

This paper describes a parallel implementation of an image feature tracking system. The system is designed to operate as the front-end of a vision system for controlling autonomous guided vehicles (AGV). Image features or tokens (edge-based line segments in the example given here) are extracted from the image and allocated to individual tracking processes. Both the extraction and the tracking stages are performed by concurrent processes. Arbitrary tracking algorithms may be associated with each process. In the current implementation, a Kalman filter is used to track and predict tokens in subsequent image frames.

Citation Download Citation

Timothy J. Ellis, Majid Mirmehdi, and Geoff R. Dowling "Tracking image features using a parallel computational model", Proc. SPIE 1708, Applications of Artificial Intelligence X: Machine Vision and Robotics, (1 March 1992); https://doi.org/10.1117/12.58571

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