Pavlos Mavridis

Using Virtual Environments to Tell the Story: "The Battle of Thermopylae"

Virtual environments have been valued as being extremely motivating for learners and therefore are employed as an innovative, more accessible framework to deliver education and entertainment to the public. Recent advances in creating videogame applications imbedded with effective learning principles, along with the evolution of human computer interfaces performed within the entertainment industry, suggests that a combination of successful practices in these areas could potentially transform virtual environments to a significant educational tool that could facilitate the learning process. This paper describes a virtual reality exhibit implemented for the museum of Thermopylae located at the site of the original battle, near the city of Lamia in Greece. We utilized storytelling techniques and principles of modern videogames to disseminate historical knowledge about the battle and the associated legends. After describing the hardware and software components comprising this installation we elaborate over the educational techniques designed to reinforce the strength of virtual reality technology as a mean of designing educational experiences in the context of historical events.

High quality elliptical texture filtering on GPU

The quality of the available hardware texture filtering, even on state of the art graphics hardware, suffers from several aliasing artifacts, in both spatial and temporal domain. Those artifacts are mostly evident in extreme conditions, such as grazing viewing angles, highly warped texture coordinates, or extreme perspective and become especially annoying when animation is involved. In this paper we introduce a method to perform high quality texture filtering on GPU, based on the theory behind the Elliptical Weighted Average (EWA) filter. Our method uses the underlying anisotropic filtering hardware of the GPU to construct a filter that closely matches the shape and the properties of the EWA filter, offering vast improvements in the quality of texture mapping while maintaining high performance. Targeting real-time applications, we also introduce a novel spatial and temporal sample distribution scheme that distributes samples in space and time, permitting the human eye to perceive a higher image quality, while using less samples on each frame. Those characteristics make our method practical for use in games and other interactive applications. For cases where quality is more important than speed, like GPU renderers and image manipulation programs, we also present an exact implementation of the EWA filter that smartly uses the underlying bilinear filtering hardware to gain a significant speedup.

Efficient Sparse ICP

The registration of two geometric surfaces is typically addressed using variants of the Iterative Closest Point (ICP) algorithm. The Sparse ICP method formulates the problem using sparsity-inducing norms, significantly improving the resilience of the registration process to large amounts of noise and outliers, but introduces a significant performance degradation. In this paper we first identify the reasons for this performance degradation and propose a hybrid optimization system that combines a Simulated Annealing search along with the standard Sparse ICP, in order to solve the underlying optimization problem more efficiently. We also provide several insights on how to further improve the overall efficiency by using a combination of approximate distance queries, parallel execution and uniform subsampling. The resulting method provides cumulative performance gain of more than one order of magnitude, as demonstrated through the registration of partially overlapping scans with various degrees of noise and outliers.

Fractured Object Reassembly via Robust Surface Registration

The reassembly of fractured 3D objects from their parts is an important problem in cultural heritage and other domains. We approach reassembly from a geometric matching perspective and propose a pipeline for the automatic solution of the problem, where an efficient and generic three-level coarse-to-fine search strategy is used for the underlying global optimization. Key to the efficiency of our approach is the use of a discretized approximation of the surfaces’ distance field, which significantly reduces the cost of distance queries and allows our method to systematically search the global parameter space with minimal cost. The resulting reassembly pipeline provides highly reliable alignment, as demonstrated through the reassembly of fractured objects from their fragments and the reconstruction of 3D objects from partial scans, showcasing the wide applicability of our methodology.

Towards automated 3D reconstruction of defective cultural heritage objects

Due to recent improvements in 3D acquisition and shape processing technology, the digitization of Cultural Heritage (CH) artifacts is gaining increased application in context of archival and archaeological research. This increasing availability of acquisition technologies also implies a need for intelligent processing methods that can cope with imperfect object scans. Specifically for Cultural Heritage objects, besides imperfections given by the digitization process, also the original artifact objects may be imperfect due to deterioration or fragmentation processes. Currently, the reconstruction of previously digitized CH artifacts is mostly performed manually by expert users reassembling fragment parts and completing imperfect objects by modeling. However, more automatic methods for CH object repair and completion are needed to cope with increasingly large data becoming available. In this conceptual paper, we first provide a brief survey of typical imperfections in CH artifact scan data and in turn motivate the need for respective repair methods. We survey and classify a selection of existing reconstruction methods with respect to their applicability for CH objects, and then discuss how these approaches can be extended and combined to address various types of physical defects that are encountered in CH artifacts by proposing a flexible repair workflow for 3D digitizations of CH objects. The workflow accommodates an automatic reassembly step which can deal with fragmented input data. It also includes the similarity-based retrieval of appropriate complementary object data which is used to repair local and global object defects. Finally, we discuss options for evaluation of the effectiveness of such a CH repair workflow.

3D object repair using 2d algorithms

A number of three-dimensional algorithms have been proposed to solve the problem of patching surfaces to rectify and extrapolate missing information due to model problems or bad geometry visibility during data capture. On the other hand, a number of similar yet more simple and robust techniques apply to 2D image data and are used for texture restoration. In this paper we make an attempt to bring these two-dimensional techniques to the 3D domain due to their obvious advantage of simplicity and controllability. Creating a depth image with the help of a voxelisation algorithm will allow us to apply a variety of image repair algorithms in order to mend a 3D object. The use of three variations of the texture synthesis algorithm is investigated. Constrained texture synthesis and its variations using the Haar wavelet and image decomposition methods are also proposed in order to preserve patterns appearing on the object while trying to maintain its geometry intact.

From Reassembly to Object Completion: A Complete Systems Pipeline

The problem of the restoration of broken artifacts, where large parts could be missing, is of high importance in archaeology. The typical manual restoration can become a tedious and error-prone process, which also does not scale well. In recent years, many methods have been proposed for assisting the process, most of which target specialized object types or operate under very strict constraints. We propose a digital shape restoration pipeline consisting of proven, robust methods for automatic fragment reassembly and shape completion of generic three-dimensional objects of arbitrary type. In this pipeline, first we introduce a novel unified approach for handling the reassembly of objects from heavily damaged fragments by exploiting both fracture surfaces and salient features on the intact sides of fragments, when available. Second, we propose an object completion procedure based on generalized symmetries and a complementary part extraction process that is suitable for driving the fabrication of missing geometry. We demonstrate the effectiveness of our approach using real-world fractured objects and software implemented as part of the European Union--funded PRESIOUS project, which is also available for download from the project site.

Object Completion using k-Sparse Optimization

We present a new method for the completion of partial globally‐symmetric 3D objects, based on the detection of partial and approximate symmetries in the incomplete input dataset. In our approach, symmetry detection is formulated as a constrained sparsity maximization problem, which is solved efficiently using a robust RANSAC‐based optimizer. The detected partial symmetries are then reused iteratively, in order to complete the missing parts of the object. A global error relaxation method minimizes the accumulated alignment errors and a non‐rigid registration approach applies local deformations in order to properly handle approximate symmetry. Unlike previous approaches, our method does not rely on the computation of features, it uniformly handles translational, rotational and reflectional symmetries and can provide plausible object completion results, even on challenging cases, where more than half of the target object is missing. We demonstrate our algorithm in the completion of 3D scans with varying levels of partiality and we show the applicability of our approach in the repair and completion of heavily eroded or incomplete cultural heritage objects.

Facet Extraction and Classification for the Reassembly of Fractured 3D Objects

The reassembly of fractured 3D objects is a critical problem in computationa l archaeology, and other application domains. An essential part of this problem is to distinguish the regions of the object that belong to the original surface from the fractured ones. A general strategy to solve this region cla ssification problem is to first divide the surface of the object into distinct facets and then classify each one of them based on statistical properties. While many relevant algorithms have been previously proposed ( [ PKT01], [ HFG∗06], [ WW08]), a comparative evaluation of some well-known segmentation strategies, when used in the co ntext f such a problem, is absent from the bibliography. In this poster we present our ongoing work on the e valuation of the performance and quality of segmentation algorithms when operating on fractured objects. We a lso present a novel method for the classification of the segmented regions to intact and fractured, based on th eir s atistical properties.

Fractured 3D object restoration and completion

The problem of object restoration from eroded fragments where large parts could be missing is of high relevance in archaeology. Manual restoration is possible and common in practice but it is a tedious and error-prone process, which does not scale well. Solutions for specific parts of the problem have been proposed but a complete reassembly and repair pipeline is absent from the bibliography. We propose a shape restoration pipeline consisting of appropriate methods for automatic fragment reassembly and shape completion. We demonstrate the effectiveness of our approach using real-world fractured objects.