Effective 3D Geometric Matching for Data Restoration and Its Forensic Application

3D geometric matching is the technique to detect the similar patterns among multiple objects. It is an important and fundamental problem and can facilitate many tasks in computer graphics and vision, including shape comparison and retrieval, data fusion, scene understanding and object recognition, and data restoration. For example, 3D scans of an object from different angles are matched and stitched together to form the complete geometry. In medical image analysis, the motion of deforming organs is modeled and predicted by matching a series of CT images. This problem is challenging and remains unsolved, especially when the similar patterns are 1) small and lack geometric saliency; 2) incomplete due to the occlusion of the scanning and damage of the data. We study the reliable matching algorithm that can tackle the above difficulties and its application in data restoration. Data restoration is the problem to restore the fragmented or damaged model to its original complete state. It is a new area and has direct applications in many scientific fields such as Forensics and Archeology. In this dissertation, we study novel effective geometric matching algorithms, including curve matching, surface matching, pairwise matching, multi-piece matching and template matching. We demonstrate its applications in an integrated digital pipeline of skull reassembly, skull completion, and facial reconstruction, which is developed to facilitate the state-of-the-art forensic skull/facial reconstruction processing pipeline in law enforcement

A computerized craniofacial reconstruction method for an unidentified skull based on statistical shape models

Craniofacial reconstruction (CFR) has been widely used to produce the facial appearance of an unidentified skull in the realm of forensic science. Many studies have indicated that the computerized CFR approach is fast, flexible, consistent and objective in comparison to the traditional manual CFR approach. This paper presents a computerized CFR system called CFRTools, which features a CFR method based on a statistical shape model (SSM) of living human head models. Given an unidentified skull, a geometrically-similar template skull is chosen as a template, and a non-registration method is used to improve the accuracy of the construction of dense corresponding vertices through the alignment of the template and the unidentified skull. Generalized Procrustes analysis (GPA) and principal component analysis (PCA) are carried out to construct the skull and face SSMs. The sex of the unidentified skull is then predicted based on skull SSM and centroid size, rather than geometric measurements based on anatomical landmarks. Furthermore, a craniofacial morphological relationship which is learnt from the principal component (PC) scores of the skull and face dataset is used to produce a possible reconstructed face. Finally, multiple possible reconstructed faces for the same skull can further be recreated based on adjusting the PC coefficients. The experimental results show that the average rate of sex classification is 97.14% and the reconstructed face of the unidentified skull can be produced. In addition, experts’ understanding and experience can be harnessed in production of face variations for the same skull, which can further be used as a reference for portraiture creation

Fantastic Breaks: A Dataset of Paired 3D Scans of Real-World Broken Objects and Their Complete Counterparts

Automated shape repair approaches currently lack access to datasets that describe real-world damaged geometry. We present Fantastic Breaks (and Where to Find Them: https://terascale-all-sensing-research-studio.github.io/FantasticBreaks), a dataset containing scanned, waterproofed, and cleaned 3D meshes for 150 broken objects, paired and geometrically aligned with complete counterparts. Fantastic Breaks contains class and material labels, proxy repair parts that join to broken meshes to generate complete meshes, and manually annotated fracture boundaries. Through a detailed analysis of fracture geometry, we reveal differences between Fantastic Breaks and synthetic fracture datasets generated using geometric and physics-based methods. We show experimental shape repair evaluation with Fantastic Breaks using multiple learning-based approaches pre-trained with synthetic datasets and re-trained with subset of Fantastic Breaks.Comment: To be published at CVPR 202

A Survey of Geometric Analysis in Cultural Heritage

We present a review of recent techniques for performing geometric analysis in cultural heritage (CH) applications. The survey is aimed at researchers in the areas of computer graphics, computer vision and CH computing, as well as to scholars and practitioners in the CH field. The problems considered include shape perception enhancement, restoration and preservation support, monitoring over time, object interpretation and collection analysis. All of these problems typically rely on an understanding of the structure of the shapes in question at both a local and global level. In this survey, we discuss the different problem forms and review the main solution methods, aided by classification criteria based on the geometric scale at which the analysis is performed and the cardinality of the relationships among object parts exploited during the analysis. We finalize the report by discussing open problems and future perspectives

Virtuální rekonstrukce, její význam a přínos k paleobiologickému studiu fosilního člověka

Zachovalost kosterního materiálu je hlavní překážkou paleoantropologických studií. Virtuální metody se od 90. let 20. století staly důležitou součástí antropologického výzkumu, přičemž značně pomáhají překonat problémy zachovalosti, a to dvěma hlavními způsoby: zlepšují extrakci informací z fragmentárního materiálu a umožňují objektivnější rekonstrukci fragmentárních a nekompletních nálezů. Tato práce se zaměřila na virtuální rekonstrukci dvou fosilních nálezů: lebky moderního člověka Zlatý kůň (ZK; Česká republika) ze svrchního paleolitu a neandertálské pánve Regourdou 1 (R1) z Francie. Rekonstrukce lebky ZK nám umožnila revidovat pohlavní diagnózu a analyzovat její morfologickou afinitu. Na základě sekundární pohlavní diagnózy byl jedinec ZK s vysokou pravděpodobností žena a lebka vykazuje afinitu k rané svrchně paleolitické populaci. Pánev R1 vykazuje značnou asymetrii, která byla nejprve analyzována na křížové kosti v porovnání se zdravými moderními lidmi a neandertálci. Asymetrie výrazně překračuje variabilitu pozorovanou v současné populaci a mohla souviset s asymetrickým přenosem zátěže. Výrazná asymetrie byla proto zohledněna při následné rekonstrukci pánve, která nám umožnila posoudit pohlaví jedince a analyzovat transverzální rozměry pánevního kanálu a orientaci křížové kosti. Na základě...Preservation is a major obstacle in paleoanthropological studies. Since 1990s virtual methods have become an important part of anthropological research helping to overcome preservation problems in two principle ways: they improve extraction of information from a fragmentary material, and they permit a more objective reconstruction of fragmentary and incomplete remains. This thesis has focused on the virtual reconstruction of two fossil specimens: the modern human cranium from the Upper Paleolithic site of Zlatý kůň (ZK; Czech Republic) and the Neandertal Regourdou 1 (R1) pelvis (France). The reconstruction of the ZK cranium allowed us to revise sex attribution and analyze morphological affinity. Based on the secondary sex diagnosis, the ZK individual was most probably a female and exhibits a great affinity to Early Upper Paleolithic population. The R1 pelvis shows considerable asymmetry that was first analyzed on the sacrum in comparison with healthy modern humans and Neandertals. The asymmetry exceeds normal variation observed in the extant population and could have related to asymmetrical load dissipation. Therefore, the asymmetry was considered in the subsequent preliminary pelvic reconstruction which allowed us to assess sex of the individual and to analyze transverse dimensions of the pelvic...Katedra antropologie a genetiky člověkaDepartment of Anthropology and Human GeneticsPřírodovědecká fakultaFaculty of Scienc

Image Processing Applications in Real Life: 2D Fragmented Image and Document Reassembly and Frequency Division Multiplexed Imaging

In this era of modern technology, image processing is one the most studied disciplines of signal processing and its applications can be found in every aspect of our daily life. In this work three main applications for image processing has been studied. In chapter 1, frequency division multiplexed imaging (FDMI), a novel idea in the field of computational photography, has been introduced. Using FDMI, multiple images are captured simultaneously in a single shot and can later be extracted from the multiplexed image. This is achieved by spatially modulating the images so that they are placed at different locations in the Fourier domain. Finally, a Texas Instruments digital micromirror device (DMD) based implementation of FDMI is presented and results are shown. Chapter 2 discusses the problem of image reassembly which is to restore an image back to its original form from its pieces after it has been fragmented due to different destructive reasons. We propose an efficient algorithm for 2D image fragment reassembly problem based on solving a variation of Longest Common Subsequence (LCS) problem. Our processing pipeline has three steps. First, the boundary of each fragment is extracted automatically; second, a novel boundary matching is performed by solving LCS to identify the best possible adjacency relationship among image fragment pairs; finally, a multi-piece global alignment is used to filter out incorrect pairwise matches and compose the final image. We perform experiments on complicated image fragment datasets and compare our results with existing methods to show the improved efficiency and robustness of our method. The problem of reassembling a hand-torn or machine-shredded document back to its original form is another useful version of the image reassembly problem. Reassembling a shredded document is different from reassembling an ordinary image because the geometric shape of fragments do not carry a lot of valuable information if the document has been machine-shredded rather than hand-torn. On the other hand, matching words and context can be used as an additional tool to help improve the task of reassembly. In the final chapter, document reassembly problem has been addressed through solving a graph optimization problem

A Framework for the Semantics-aware Modelling of Objects

The evolution of 3D visual content calls for innovative methods for modelling shapes based on their intended usage, function and role in a complex scenario. Even if different attempts have been done in this direction, shape modelling still mainly focuses on geometry. However, 3D models have a structure, given by the arrangement of salient parts, and shape and structure are deeply related to semantics and functionality. Changing geometry without semantic clues may invalidate such functionalities or the meaning of objects or their parts. We approach the problem by considering semantics as the formalised knowledge related to a category of objects; the geometry can vary provided that the semantics is preserved. We represent the semantics and the variable geometry of a class of shapes through the parametric template: an annotated 3D model whose geometry can be deformed provided that some semantic constraints remain satisfied. In this work, we design and develop a framework for the semantics-aware modelling of shapes, offering the user a single application environment where the whole workflow of defining the parametric template and applying semantics-aware deformations can take place. In particular, the system provides tools for the selection and annotation of geometry based on a formalised contextual knowledge; shape analysis methods to derive new knowledge implicitly encoded in the geometry, and possibly enrich the given semantics; a set of constraints that the user can apply to salient parts and a deformation operation that takes into account the semantic constraints and provides an optimal solution. The framework is modular so that new tools can be continuously added. While producing some innovative results in specific areas, the goal of this work is the development of a comprehensive framework combining state of the art techniques and new algorithms, thus enabling the user to conceptualise her/his knowledge and model geometric shapes. The original contributions regard the formalisation of the concept of annotation, with attached properties, and of the relations between significant parts of objects; a new technique for guaranteeing the persistence of annotations after significant changes in shape's resolution; the exploitation of shape descriptors for the extraction of quantitative information and the assessment of shape variability within a class; and the extension of the popular cage-based deformation techniques to include constraints on the allowed displacement of vertices. In this thesis, we report the design and development of the framework as well as results in two application scenarios, namely product design and archaeological reconstruction