Automatic Orientation of Large Blocks of Oblique Images

Abstract

ABSTRACT:Nowadays, multi-camera platforms combining nadir and oblique cameras are experiencing a revival. Due to their advantages such as ease of interpretation, completeness through mitigation of occluding areas, as well as system accessibility, they have found their place in numerous civil applications. However, automatic post-processing of such imagery still remains a topic of research. Configuration of cameras poses a challenge on the traditional photogrammetric pipeline used in commercial software and manual measurements are inevitable. For large image blocks it is certainly an impediment. Within theoretical part of the work we review three common least square adjustment methods and recap on possible ways for a multi-camera system orientation. In the practical part we present an approach that successfully oriented a block of 550 images acquired with an imaging system composed of 5 cameras (Canon Eos 1D Mark III) with different focal lengths. Oblique cameras are rotated in the four looking directions (forward, backward, left and right) by 45• with respect to the nadir camera. The workflow relies only upon open-source software: a developed tool to analyse image connectivity and Apero to orient the image block. The benefits of the connectivity tool are twofold: in terms of computational time and success of Bundle Block Adjustment. It exploits the georeferenced information provided by the Applanix system in constraining feature point extraction to relevant images only, and guides the concatenation of images during the relative orientation. Ultimately an absolute transformation is performed resulting in mean re-projection residuals equal to 0.6pix.

CHANGING THE PRODUCTION PIPELINE – USE OF OBLIQUE AERIAL CAMERAS FOR MAPPING PURPOSES

“…At scientific level, investigations have focused on the quality of the images, on acquisition geometry, on block triangulation accuracy and Dense Image Matching (DIM). Research topics include optimal viewing angles of the oblique sensor heads (in relation to surface characteristics), optimal overlaps between images and strips, tie point extraction approaches, and image orientation strategies, and have been reported in a number of publications (Jacobsen, 2008;Gerke and Nyaruhuma, 2009;Wiedemann and More, 2012;Rupnik et al, 2013;Rupnik et al, 2015). Given the increased number of oblique cameras on the market and the increased use of oblique imagery, software providers have updated the standard algorithms designed for vertical imagery, e.g.…”

OBLIQUE AERIAL IMAGERY FOR NMA – SOME BEST PRACTICES

“…Since some years, FBK Trento and ITC/Twente University are both running investigations on aerial oblique imagery (Gerke and Nyaruhuma, 2009;Nyaruhuma et al, 2012;Xiao et al, 2012;Rupnik et al, 2013;Rupnik et al, 2014;Remondino and Gerke, 2015;Rupnik et al, 2015). The studies are driven by the clear problems in processing oblique image blocks and by the numerous applications opened-up by oblique aerial views.…”

Building Footprints Extraction from Oblique Imagery

“…), or simply aligning the (not adjusted) oblique cameras to the (adjusted) nadir ones with the use of known relative position between images (Wiedemann and More, 2012). More recently other investigations have succeeded to automatically orient large image blocks with commercial (Fritsch et al, 2012) or open-source packages (Rupnik et al, 2013). Other research works have investigated the quality and the accuracy of the point clouds and successive products (e.g.…”

“…In this paper a fully automatic methodology for building footprints extraction from oblique imagery is described. A reliable orientation procedure (Rupnik et al, 2013) is first applied and then dense point clouds are derived. The verticality of building façades is then exploited to detect buildings (filtering out the vegetation) and define their footprints in a reliable way for very different typologies of buildings.…”