Optimizing rectangular-shaped object tracking with subpixel resolution

Belen Ferrer; Jorge Perez; David Mas; Julian Espinosa

doi:10.1117/12.2555004

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1 April 2020 Optimizing rectangular-shaped object tracking with subpixel resolution

Belen Ferrer, Jorge Perez, David Mas, Julian Espinosa

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Proceedings Volume 11353, Optics, Photonics and Digital Technologies for Imaging Applications VI; 113531R (2020) https://doi.org/10.1117/12.2555004
Event: SPIE Photonics Europe, 2020, Online Only

Abstract

Object tracking with subpixel accuracy often needs targets with special shapes, which include random dot patterns, circular objects or targets with irregular contours. Unfortunately, in majority of real applications no such objects are found or cannot be attached to the region of interest and non-optimal objects must be used. Among those, we will analyze here the performance of rectangular objects that may be common in natural or artificial targets. Object tracking has been performed through the two most common methods that appear in the literature: centroid calculation and cross-correlation with peak interpolation. Numerical simulations show that tracking results for such objects are highly dependent of the object orientation with respect to the direction of movement. This is due to the interference of the object borders and the sensor and how is the subpixel information obtained. Best results are obtained for object orientations from 5 to 30 deg with respect to the normal to the displacement directions. Experimental results confirm the simulations and allow us to establish that, although object alignment provides a better image on the sensor with sharper borders, this situation is not desirable for accurate subpixel tracking, with accuracies varying from accuracies of 0.08 px (RMS error) with aligned objects to 0.02px with a misaligned target.

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Belen Ferrer, Jorge Perez, David Mas, and Julian Espinosa "Optimizing rectangular-shaped object tracking with subpixel resolution", Proc. SPIE 11353, Optics, Photonics and Digital Technologies for Imaging Applications VI, 113531R (1 April 2020); https://doi.org/10.1117/12.2555004

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