Abstract
An important goal in applications such as photogrammetry is precise kinematic state estimation (position, orientation, and velocity) of complex moving objects, given a sequence of images. Currently, no method achieves the precision and accuracy of manual tracking under difficult real-world conditions. In this work, we describe a promising new direction of research that processes the 3D datacube formed from the sequence of images and uses edge detectors to validate position hypotheses. We propose a variety of new 3D edge/surface detectors, including new variants of wavelet- and shearlet-based detectors and hybrid 3D detectors that provide computational efficiency. The edge detectors tend to produce broad edges, increasing the uncertainty in the state estimates. We overcome this limitation by finding the best match of the edge image from the 3D data to edge images derived from different state hypotheses. We demonstrate that our new 3D state trackers outperform those that only use 2D information, even under the challenge of changing lighting conditions.
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Acknowledgements
D.P.O acknowledges partial support from the National Science Foundation under grant NSF DMS 1016266.
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Schug, D.A., Easley, G.R., O’Leary, D.P. (2017). Precise State Tracking Using Three-Dimensional Edge Detection. In: Balan, R., Benedetto, J., Czaja, W., Dellatorre, M., Okoudjou, K. (eds) Excursions in Harmonic Analysis, Volume 5. Applied and Numerical Harmonic Analysis. Birkhäuser, Cham. https://doi.org/10.1007/978-3-319-54711-4_4
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DOI: https://doi.org/10.1007/978-3-319-54711-4_4
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