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Real-time model-based tracking combining spatial and temporal features

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Abstract

This paper describes a method for tracking moving image features by combining spatial and temporal edge information with model-based feature information. The algorithm updates the two-dimensional position of object features by correlating predicted model features with current image data. The results of the correlation process are used to compute an updated model. The algorithm makes use of a high temporal sampling rate with respect to spatial changes of the image features and operates in a real-time multi-processing environment. Preliminary results demonstrate successful tracking for image feature velocities between 1.1 and 4.5 pixels every image frame.

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Authors and Affiliations

  1. Robot Systems Division, National Institute of Standards and Technology, 20899, Gaithersburg, MD, USA

    Karen Roberts & Marilyn Nashman

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  1. Karen Roberts
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  2. Marilyn Nashman
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Roberts, K., Nashman, M. Real-time model-based tracking combining spatial and temporal features. Journal of Intelligent and Robotic Systems 5, 25–38 (1992). https://doi.org/10.1007/BF00357128

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  • DOI: https://doi.org/10.1007/BF00357128

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