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Item Interactive Facades - Analysis and Synthesis of Semi-Regular Facades(The Eurographics Association and Blackwell Publishing Ltd., 2013) AlHalawani, Sawsan; Yang, Yong-Liang; Liu, Han; Mitra, Niloy J.; I. Navazo, P. PoulinUrban facades regularly contain interesting variations due to allowed deformations of repeated elements (e.g., windows in different open or close positions) posing challenges to state-of-the-art facade analysis algorithms. We propose a semi-automatic framework to recover both repetition patterns of the elements and their individual deformation parameters to produce a factored facade representation. Such a representation enables a range of applications including interactive facade images, improved multi-view stereo reconstruction, facade-level change detection, and novel image editing possibilities.Item Smart Variations: Functional Substructures for Part Compatibility(The Eurographics Association and Blackwell Publishing Ltd., 2013) Zheng, Youyi; Cohen-Or, Daniel; Mitra, Niloy J.; I. Navazo, P. PoulinAs collections of 3D models continue to grow, reusing model parts allows generation of novel model variations. Naïvely swapping parts across models, however, leads to implausible results, especially when mixing parts across different model families. Hence, the user has to manually ensure that the final model remains functionally valid. We claim that certain symmetric functional arrangements (SFARR-s), which are special arrangements among symmetrically related substructures, bear close relation to object functions. Hence, we propose a purely geometric approach based on such substructures to match, replace, and position triplets of parts to create non-trivial, yet functionally plausible, model variations. We demonstrate that starting even from a small set of models such a simple geometric approach can produce a diverse set of non-trivial and plausible model variations.Item Sketch-to-Design: Context-Based Part Assembly(The Eurographics Association and Blackwell Publishing Ltd., 2013) Xie, Xiaohua; Xu, Kai; Mitra, Niloy J.; Cohen-Or, Daniel; Gong, Wenyong; Su, Qi; Chen, Baoquan; Holly Rushmeier and Oliver DeussenDesigning 3D objects from scratch is difficult, especially when the user intent is fuzzy and lacks a clear target form. We facilitate design by providing reference and inspiration from existing model contexts. We rethink model design as navigating through different possible combinations of part assemblies based on a large collection of pre‐segmented 3D models. We propose an interactive sketch‐to‐design system, where the user sketches prominent features of parts to combine. The sketched strokes are analysed individually, and more importantly, in context with the other parts to generate relevant shape suggestions via adesign galleryinterface. As a modelling session progresses and more parts get selected, contextual cues become increasingly dominant, and the model quickly converges to a final form. As a key enabler, we use pre‐learned part‐based contextual information to allow the user to quickly explore different combinations of parts. Our experiments demonstrate the effectiveness of our approach for efficiently designing new variations from existing shape collections.Designing 3D objects from scratch is difficult, especially when the user intent is fuzzy and lacks a clear target form. We facilitate design by providing reference and inspiration from existing model contexts. We rethink model design as navigating through different possible combinations of part assemblies based on a large collection of pre‐segmented 3D models. We propose an interactive sketch‐to‐design system, where the user sketches prominent features of parts to combine. The sketched strokes are analyzed individually, and more importantly, in context with the other parts to generate relevant shape suggestions via a design gallery interface. As a modeling session progresses and more parts get selected, contextual cues become increasingly dominant, and the model quickly converges to a final form. As a key enabler, we use pre‐learned part‐based contextual information to allow the user to quickly explore different combinations of parts.Item Symmetry in 3D Geometry: Extraction and Applications(The Eurographics Association and Blackwell Publishing Ltd., 2013) Mitra, Niloy J.; Pauly, Mark; Wand, Michael; Ceylan, Duygu; Holly Rushmeier and Oliver DeussenThe concept of symmetry has received significant attention in computer graphics and computer vision research in recent years. Numerous methods have been proposed to find, extract, encode and exploit geometric symmetries and high‐level structural information for a wide variety of geometry processing tasks. This report surveys and classifies recent developments in symmetry detection. We focus on elucidating the key similarities and differences between existing methods to gain a better understanding of a fundamental problem in digital geometry processing and shape understanding in general. We discuss a variety of applications in computer graphics and geometry processing that benefit from symmetry information for more effective processing. An analysis of the strengths and limitations of existing algorithms highlights the plenitude of opportunities for future research both in terms of theory and applications.The concept of symmetry has received significant attention in computer graphics and computer vision research in recent years. Numerous methods have been proposed to find, extract, encode, and exploit geometric symmetries and high‐level structural information for a wide variety of geometry processing tasks. This report surveys and classifies recent developments in symmetry detection. We focus on elucidating the key similarities and differences between existing methods to gain a better understanding of a fundamental problem in digital geometry processing and shape understanding in general.Item Graph Abstraction for Simplified Proofreading of Slice-based Volume Segmentation(The Eurographics Association, 2013) Sicat, Ronell B.; Hadwiger, Markus; Mitra, Niloy J.; M.- A. Otaduy and O. SorkineVolume segmentation is an integral data analysis tool in experimental science. For example, in neuroscience, analysis of 3D volumes of neural structures from electron microscopy data is a key analysis step. Despite advances in computational methods, experts still prefer to manually proofread and correct the automatic segmentation outputs. Such corrections are often annotated at the level of data slices in order to minimize distortion artifacts and effectively handle the massive data volumes. In absence of crucial global context in 3D, such a workflow remains tedious, time consuming, and error prone. In this paper, we present a simple graph-based abstraction for segmentation volumes leading to an interactive proofreading tool making the process simpler, faster, and intuitive. Starting from an initial volume segmentation, we first construct a graph abstraction and then use it to identify potential problematic regions for the user to investigate and correct spurious segmentations, if identified. We also use the graph to suggest automatic corrections, thus drastically simplifying the proofreading effort. We implemented the proofreading tool as an Avizo c plugin and evaluated the method on complex real-world use cases.Item Structure-Aware Shape Processing(The Eurographics Association, 2013) Mitra, Niloy J.; Wand, Michael; Zhang, Hao; Cohen-Or, Daniel; Bokeloh, Martin; M. Sbert and L. Szirmay-KalosShape structure is about the arrangement and relations between shape parts. Structure-aware shape processing goes beyond local geometry and low level processing, and analyzes and processes shapes at a high level. It focuses more on the global inter and intra semantic relations among the parts of shape rather than on their local geometry. With recent developments in easy shape acquisition, access to vast repositories of 3D models, and simple-to-use desktop fabrication possibilities, the study of structure in shapes has become a central research topic in shape analysis, editing, and modeling. A whole new line of structure-aware shape processing algorithms has emerged that base their operation on an attempt to understand such structure in shapes. The algorithms broadly consist of two key phases: an analysis phase, which extracts structural information from input data; and a (smart) processing phase, which utilizes the extracted information for exploration, editing, and synthesis of novel shapes. In this survey paper, we organize, summarize, and present the key concepts and methodological approaches towards efficient structure-aware shape processing. We discuss common models of structure, their implementation in terms of mathematical formalism and algorithms, and explain the key principles in the context of a number of state-ofthe- art approaches. Further, we attempt to list the key open problems and challenges, both at the technical and at the conceptual level, to make it easier for new researchers to better explore and contribute to this topic. Our goal is to both give the practitioner an overview of available structure-aware shape processing techniques, as well as identify future research questions in this important, emerging, and fascinating research area.Item Guided Real-Time Scanning of Indoor Objects(The Eurographics Association and Blackwell Publishing Ltd., 2013) Kim, Young Min; Mitra, Niloy J.; Huang, Qixing; Guibas, Leonidas; B. Levy, X. Tong, and K. YinAdvances in 3D acquisition devices provide unprecedented opportunities for quickly scanning indoor environments. Such raw scans, however, are often noisy, incomplete, and significantly corrupted, making semantic scene understanding difficult, if not impossible. Unfortunately, in most existing workflows, scan quality is assessed after the scanning stage is completed, making it cumbersome to correct for significant missing data by additional scanning. In this work, we present a guided real-time scanning setup, wherein the incoming 3D data stream is continuously analyzed, and the data quality is automatically assessed. While the user is scanning an object, the proposed system discovers and highlights potential missing parts, thus guiding the operator (or an autonomous robot) as where to scan next. The proposed system assesses the quality and completeness of the 3D scan data by comparing to a large collection of commonly occurring indoor man-made objects using an efficient, robust, and effective scan descriptor. We have tested the system on a large number of simulated and real setups, and found the guided interface to be effective even in cluttered and complex indoor environments.