Abstract
We propose a new design for an optical coded target based on concentric circles and a position and orientation determination algorithm optimized for high distances compared to the target size. If two ellipses are fitted on the edge pixels corresponding to the outer and inner circles, quasi-analytical methods are known to obtain the coordinates of the projection of the circles center. We show the limits of these methods for quasi-frontal target orientations and in presence of noise and we propose an iterative refinement algorithm based on a geometric invariant. Next, we introduce a closed form, computationally inexpensive, solution to obtain the target position and orientation given the projected circle center and the parameters of the outer circle projection. The viability of the approach is demonstrated based on aerial pictures taken by an UAV from elevations between 10 to 100 m. We obtain a distance RMS below 0.25 % under 50 m and below 1 % under 100 m with a target size of 90 cm, part of which is a deterministic bias introduced by image exposure.
Highlights
Optical coded targets consist in distinctive visual patterns designed to be automatically detected and measured in camera images
Even tough visual targets are well studied in the literature, this field is still fertile for research in specific applications such as camera calibration, photogrammetry, robotics, augmented reality and in machine vision techniques in general
In this work we propose a design for an optical target and a novel detection and measuring algorithm for which the requirements are driven by a specific application within the mapKITE project1
Summary
Optical coded targets consist in distinctive visual patterns designed to be automatically detected and measured in camera images. In this work we propose a design for an optical target and a novel detection and measuring algorithm for which the requirements are driven by a specific application within the mapKITE project. In this work we propose a design for an optical target and a novel detection and measuring algorithm for which the requirements are driven by a specific application within the mapKITE project1 In this project, a new mapping paradigm is introduced in which a terrestrial-aerial tandem, composed by a human driven terrain vehicle (TV), and an autonomous micro aerial vehicle (UAV), performs the surveys, augmenting terrestrial laser range-finder data with a aerial photography (Molina et al, 2015). ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume III-3, 2016 XXIII ISPRS Congress, 12–19 July 2016, Prague, Czech Republic reference image
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