I. Kalisperakis

Generation of Orthoimages and Perspective Views with Automatic Visibility Checking and Texture Blending

Conventional orthorectification software cannot handle surface occlusions and image visibility. The approach presented here synthesizes related work in photogrammetry and computer graphics/vision to automatically produce orthographic and perspective views based on fully 3D surface data (supplied by laser scanning). Surface occlusions in the direction of projection are detected to create the depth map of the new image. This information allows identifying, by visibility checking through back-projection of surface triangles, all source images which are entitled to contribute color to each pixel of the novel image. Weighted texture blending allows regulating the local radiometric contribution of each source image involved, while outlying color values are automatically discarded with a basic statistical test. Experimental results from a close-range project indicate that this fusion of laser scanning with multiview photogrammetry could indeed combine geometric accuracy with high visual quality and speed. A discussion of intended improvements of the algorithm is also included.

Stereo matching based on census transformation of image gradients

Although multiple-view matching provides certain significant advantages regarding accuracy, occlusion handling and radiometric fidelity, stereo-matching remains indispensable for a variety of applications; these involve cases when image acquisition requires fixed geometry and limited number of images or speed. Such instances include robotics, autonomous navigation, reconstruction from a limited number of aerial/satellite images, industrial inspection and augmented reality through smart-phones. As a consequence, stereo-matching is a continuously evolving research field with growing variety of applicable scenarios. In this work a novel multi-purpose cost for stereo-matching is proposed, based on census transformation on image gradients and evaluated within a local matching scheme. It is demonstrated that when the census transformation is applied on gradients the invariance of the cost function to changes in illumination (non-linear) is significantly strengthened. The calculated cost values are aggregated through adaptive support regions, based both on cross-skeletons and basic rectangular windows. The matching algorithm is tuned for the parameters in each case. The described matching cost has been evaluated on the Middlebury stereo-vision 2006 datasets, which include changes in illumination and exposure. The tests verify that the census transformation on image gradients indeed results in a more robust cost function, regardless of aggregation strategy.

3D city models completion by fusing lidar and image data

A fundamental step in the generation of visually detailed 3D city models is the acquisition of high fidelity 3D data. Typical approaches employ DSM representations usually derived from Lidar (Light Detection and Ranging) airborne scanning or image based procedures. In this contribution, we focus on the fusion of data from both these methods in order to enhance or complete them. Particularly, we combine an existing Lidar and orthomosaic dataset (used as reference), with a new aerial image acquisition (including both vertical and oblique imagery) of higher resolution, which was carried out in the area of Kallithea, in Athens, Greece. In a preliminary step, a digital orthophoto and a DSM is generated from the aerial images in an arbitrary reference system, by employing a Structure from Motion and dense stereo matching framework. The image-to-Lidar registration is performed by 2D feature (SIFT and SURF) extraction and matching among the two orthophotos. The established point correspondences are assigned with 3D coordinates through interpolation on the reference Lidar surface, are then backprojected onto the aerial images, and finally matched with 2D image features located in the vicinity of the backprojected 3D points. Consequently, these points serve as Ground Control Points with appropriate weights for final orientation and calibration of the images through a bundle adjustment solution. By these means, the aerial imagery which is optimally aligned to the reference dataset can be used for the generation of an enhanced and more accurately textured 3D city model.

An interactive story map for the Methana volcanic peninsula

The purpose of this research is the identification, recording, mapping and photographic imaging of the special volcanic geoforms as well as the cultural monuments of the volcanic Methana Peninsula. With the use of novel methods the aim is to reveal and study the impressive topographic features of the Methana geotope and discover its unique geodiversity. The proposed hiking trails along with the Methana’s archaeology and history, will be highlighted through the creation of an ‘intelligent’ interactive map (Story Map). Two field trips have been conducted for the collection of further information and the digital mapping of the younger volcanic flows of Kammeni Chora with drones. Through the compiled data, thematic maps were created depicting the lava flows and the most important points of the individual hiking paths. The thematic maps were created using a Geographic Information System (GIS). Finally, those maps were the basis for the creation of the main Story Map. The decision to use Story Maps was based on the numerous advantages on offer such as user-friendly mapping, ease of use and interaction and user customized displays.