Dr. Ilias Kalisperakis Profile

Dr. Ilias Kalisperakis

at Technological Educational Institute of Athens

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Publications (2)

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Proceedings Article | 21 June 2015 Paper

Stereo matching based on census transformation of image gradients

C. Stentoumis, L. Grammatikopoulos, I. Kalisperakis, G. Karras, E. Petsa

Proceedings Volume 9528, 95280Q (2015) https://doi.org/10.1117/12.2184763

KEYWORDS: Binary data, Image filtering, Photogrammetry, Reconstruction algorithms, Algorithm development, Image acquisition, Robotics, Inspection, Augmented reality, Image analysis

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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.

Proceedings Article | 21 June 2015 Paper

3D city models completion by fusing lidar and image data

L. Grammatikopoulos, I. Kalisperakis, E. Petsa, C. Stentoumis

Proceedings Volume 9528, 95280O (2015) https://doi.org/10.1117/12.2184722

KEYWORDS: 3D modeling, LIDAR, 3D image processing, Data modeling, 3D image enhancement, Orthophoto maps, Image registration, Image enhancement, 3D acquisition, Airborne remote sensing

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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.

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