Abstract
Abstract. The demand for 3D models of various scales and precisions is strong for a wide range of applications, among which cultural heritage recording is particularly important and challenging. In this context, dense image matching is a fundamental task for processes which involve image-based reconstruction of 3D models. Despite the existence of commercial software, the need for complete and accurate results under different conditions, as well as for computational efficiency under a variety of hardware, has kept image-matching algorithms as one of the most active research topics. Semi-global matching (SGM) is among the most popular optimization algorithms due to its accuracy, computational efficiency, and simplicity. A challenging aspect in SGM implementation is the determination of smoothness constraints, i.e. penalties P1, P2 for disparity changes and discontinuities. In fact, penalty adjustment is needed for every particular stereo-pair and cost computation. In this work, a novel formulation of self-adjusting penalties is proposed: SGM penalties can be estimated solely from the statistical properties of the initial disparity space image. The proposed method of self-adjusting penalties (SGM-SAP) is evaluated using typical cost functions on stereo-pairs from the recent Middlebury dataset of interior scenes, as well as from the EPFL Herz-Jesu architectural scenes. Results are competitive against the original SGM estimates. The significant aspects of self-adjusting penalties are: (i) the time-consuming tuning process is avoided; (ii) SGM can be used in image collections with limited number of stereo-pairs; and (iii) no heuristic user intervention is needed.
Highlights
The extraction of dense 3D information and the accurate visual recording from a set of images is a core part in various Cultural Heritage applications
Regarding the definition of cost penalties, a class of Semi-global matching (SGM) variations is dedicated to the development of functions for the adjustment of penalty P2, which is imposed on disparity changes between neighbouring pixels larger than 1 pixel; they have been reviewed in detail by Stentoumis et al (2015)
This work has presented a novel approach (SGM-SAP) aiming at the self-adjustment of penalty values of Semi-Global Matching for any image pair for any matching cost method
Summary
The extraction of dense 3D information and the accurate visual recording from a set of images is a core part in various Cultural Heritage applications. An evaluation of stereo-matching methods based on their actual results and usefulness in real life applications is quite difficult and depends on several diverging criteria. This is true if one considers the variety of both applications and arising issues, e.g. depth variability, lighting conditions, reflecting surfaces, scene occlusions, image acquisition geometry, and illumination changes, just to name a few. The presented method of self-adjusting penalties (SGM-SAP) was evaluated using internal stereo-images from the Middlebury online evaluation platform datasets, as well as images from external architectural scenes selected from the EPFL multi-view datasets.
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