Single image orientation of UAV's imagery using orthogonal projection model

Agust

2018

EECSI

In this paper, we study the influence of varying baseline components on the accuracy of a relative rotation between two overlapping aerial images taken form unmanned aerial vehicle (UAV) flight. The case is relevant when mosaicking UAV's aerial images by registering each individual image. Geotagged images facilitated by a navigational grade GPS receiver on board inform the camera position when taking pictures. However, these low accuracies of geographical coordinates encoded in an EXIF format are unreliable to depict baseline vector components between subsequent overlapping images. This research investigates these influences on the stability of rotation elements when the vector components are entered into a standard coplanarity condition equation to determine the relative rotation of the stereo images. Assuming a nadir looking camera on board while the UAV platform is flying at a constant height, the resulted vector directions are utilized to constraint the coplanarity equation. A detailed analysis of each variation is given. Our experiments based on real datasets confirm that the relative rotation between two successive overlapping images is practically unaffected by the accuracy of positioning method. Furthermore, the coplanarity constraint is invariant with respect to a translation along the baseline of the aerial stereo images.

Section: Results and Analysismentioning

confidence: 99%

A Relative Rotation between Two Overlapping UAV's Images

Agust

2018

EECSI

“…Here i and j represent information pertaining to the i ℎ image out of the m images [17,19] and relative orientation methods [20,21], whereas a spatial position of the object space points are calculated by space intersection [22]. The generation of initial approximate values for all parameters is required in (1) because the photogrammetric observation equations are non-linear with respect to the parameters and must be iteratively solved using a linearized set of equations.…”

Section: Methodsmentioning

confidence: 99%

Cadastral Surveys with Non-metric Camera Using Uav: A Feasibility Study

Rokhmana

Agustina

2019

KEG

Orthophoto maps are believed by mapping communities as a favorable media to generate land parcel boundaries for cadaster survey related projects. However, since burgeoning off-the-shelf cameras mounted on the unmanned aerial vehicle (UAV) are commonly utilized for photographing such boundaries, unreliable and unstable intrinsic parameters of these non-metric cameras impede good quality orthophoto productions. This paper presents an alternative method to measure the boundaries reliably without an existence of the orthophoto. A degraded quality of the orthophoto can be circumvented by our newly proposed method so called direct visual referencing. This method comprises two stages. The first step is to perform on the fly camera calibration to minimize instabilities of the intrinsic components of the non-metric camera. Modifying common and widely known flying paths for aerial photogrammetry mission is enabling a block variant self-calibrating bundle adjustments to proceed. The second step is a digitation process. Carefully selected Premark or prominent features along the boundaries are digitized on arbitrary selected images. These features are then matched to the similar ones onto all available images by performing multi photo geometrically constraint least squares image matching. Final results are 3D coordinates from the multi photos triangulation process. These boundaries coordinates are compared against the GPS-RTK measurements on the field. Deviations of these types of coordinates are around 1 cm. It is obvious that this method meets the precision requirement of the GPS-RTK measurements. Therefore we firmly believed that conducting UAV’s cadastral surveys using direct visual referencing is very promising in the near future.

“…Hence it is possible to express all the nine elements in terms of three independent parameters. There are wellknown methods [52] of imposing orthogonality constraints on a reduction to three independent parameters [33], but these introduce other circular functions of parameters [40] and make the direct solution sets of ( 7) or ( 9) harder to solve [53], [54]. Alternatively, the orthogonal matrix 2 is expressed with respect to three independent parameters in the form of a rational algebraic relation only.…”

Section: Methodsmentioning

confidence: 99%

Fast and stable direct relative orientation of UAV-based stereo pair

Int. J. Adv. Intell. Informatics

Agustina

2019

Self Cite

Coplanarity-based relative orientation (RO) is one of the most crucial processes to obtain reliable 3D model and point clouds in Computer Vision and Photogrammetry community. Whilst a classical and rigorous procedure requires very close approximate values of five independent parameters, a direct method needs additional constraints to solve the parameters. This paper proposes a new approach that facilitates a very fast but stable and accurate solution from five point correspondences between two overlapping aerial images taken form unmanned aerial vehicle (UAV) flight. Furthermore, if 3D coordinates of perspective centers are available form geotagged images, rotational elements of the RO parameters can be quickly solved using three correspondences only. So it is very reliable for a provision of closed-form solutions for the rigorous methods. Our formulation regards Thompson’s parameterizations of Euler angles in composing a coplanarity condition. Nonlinear terms are subsequently added into a stereo parallax within a constant term under a linear least squares criteria. This strategy is considered new as compared with the known literatures since the proposed approach can find optimal solution. Results from real datasets confirm that our method produces a fast, stable and reliable linear solution by using at least five correspondences or even only three conjugate points of geotagged image pairs.