Title :
New Depth From Focus Filters in Active Monocular Vision Systems for Indoor 3-D Tracking
Author :
Gaspar, Tiago ; Oliveira, Paulo
Author_Institution :
Inst. Super. Tecnico, Univ. de Lisboa, Lisbon, Portugal
Abstract :
In this paper, new methodologies for the estimation of the depth of a target with unknown dimensions, based on depth from focus strategies, are proposed. The measurements are extracted from images acquired with a single camera, resorting to the minimization of a new functional, deeply rooted on the optical characteristics of the lens system. The analysis and synthesis of two complementary filters and a linear parametrically varying observer are discussed in detail. These estimators use information present on the boundary of the target, which is assumed to be on a plane parallel to the camera sensor, and whose dimensions are considered to remain constant over time. This paper complements a single pan and tilt camera-based indoor positioning and tracking system. To assess the performance of the proposed solutions, a series of indoor experimental tests for a range of operation of up to ten meters, which included tracking and localizing a small unmanned aerial vehicle with unknown dimensions, was carried out. Depth estimates with accuracies on the order of a few centimeters were obtained.
Keywords :
cameras; computer vision; image filtering; indoor environment; linear parameter varying systems; object tracking; active monocular vision systems; camera sensor; complementary filters; focus filters; functional minimization; indoor 3D tracking; lens system; linear parametrically varying observer; optical characteristics; pan-and-tilt camera-based indoor positioning system; small unmanned aerial vehicle localization; target boundary; target depth estimation; target dimensions; tracking system; Accuracy; Apertures; Cameras; Cost function; Estimation; Lenses; Target tracking; Complementary filtering; depth from focus; linear-parameter-varying (LPV) observers; monocular vision systems; positioning and tracking; sensor fusion; sensor fusion.;
Journal_Title :
Control Systems Technology, IEEE Transactions on
DOI :
10.1109/TCST.2015.2388956