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Bedrich Benes - One of the best experts on this subject based on the ideXlab platform.
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dendry a Procedural Model for dendritic patterns
Interactive 3D Graphics and Games, 2019Co-Authors: Mathieu Gaillard, Bedrich Benes, Eric Guerin, Eric Galin, Damien Rohmer, Mariepaule CaniAbstract:We introduce Dendry, a Procedural function that generates dendritic patterns and is locally computable. The function is controlled by parameters such as the level of branching, the degree of local smoothing, random seeding and local disturbance parameters, and the range of the branching angles. It is also controlled by a global control function that defines the overall shape and can be used, for example, to initialize local minima. The algorithm returns the distance to a tree structure which is implicitly constructed on the fly, while requiring a small memory footprint. The evaluation can be performed in parallel for multiple points and scales linearly with the number of cores. We demonstrate an application of our Model to the generation of terrain heighfields with consistent river networks. A quad core implementation of our algorithm takes about ten seconds for a 512 × 512 resolution grid on the CPU.
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Interactive sketching of urban Procedural Models
ACM Transactions on Graphics, 2016Co-Authors: Nishida, Daniel G. Aliaga, Ignacio Garcia-dorado, Bedrich Benes, Adrien BousseauAbstract:3D Modeling remains a notoriously difficult task for novices despite significant research effort to provide intuitive and automated systems. We tackle this problem by combining the strengths of two popular domains: sketch-based Modeling and Procedural Modeling. On the one hand, sketch-based Modeling exploits our ability to draw but requires detailed, unambiguous drawings to achieve complex Models. On the other hand, Procedural Modeling automates the creation of precise and detailed geometry but requires the tedious definition and parameterization of Procedural Models. Our system uses a collection of simple Procedural grammars, called snippets, as building blocks to turn sketches into realistic 3D Models. We use a machine learning approach to solve the inverse problem of finding the Procedural Model that best explains a user sketch. We use non-photorealistic rendering to generate artificial data for training convolutional neural networks capable of quickly recognizing the Procedural rule intended by a sketch and estimating its parameters. We integrate our algorithm in a coarse-to-fine urban Modeling system that allows users to create rich buildings by successively sketching the building mass, roof, facades, windows, and ornaments. A user study shows that by using our approach non-expert users can generate complex buildings in just a few minutes.
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Proceduralization for Editing 3D Architectural Models
2016 Fourth International Conference on 3D Vision (3DV), 2016Co-Authors: İlke Demir, Daniel G. Aliaga, Bedrich BenesAbstract:Inverse Procedural Modeling discovers a Procedural representation of an existing geometric Model and the discovered Procedural Model then supports synthesizing new similar Models. We introduce an automatic approach that generates a compact, efficient, and re-usable Procedural representation of a polygonal 3D architectural Model. This representation is then used for structure-aware editing and synthesis of new geometric Models that resemble the original. Our framework captures the pattern hierarchy of the input Model into a split tree data representation. A context-free split grammar, supporting a hierarchical nesting of Procedural rules, is extracted from the tree, which establishes the base of our interactive Procedural editing engine. We show the application of our approach to a variety of architectural structures obtained by Procedurally editing web-sourced Models. The grammar generation takes a few minutes even for the most complex input and synthesis is fully interactive for buildings composed of up to 200k polygons.
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Inverse Procedural Modelling of Trees
Computer Graphics Forum, 2014Co-Authors: Ondrej Stava, Sören Pirk, Julian Kratt, Baoquan Chen, Oliver Deussen, Bedrich BenesAbstract:Procedural tree Models have been popular in computer graphics for their ability to generate a variety of output trees from a set of input parameters and to simulate plant interaction with the environment for a realistic placement of trees in virtual scenes. However, defining such Models and their parameters is a difficult task. We propose an inverse Modelling approach for stochastic trees that takes polygonal tree Models as input and estimates the parameters of a Procedural Model so that it produces trees similar to the input. Our framework is based on a novel parametric Model for tree generation and uses Monte Carlo Markov Chains to find the optimal set of parameters. We demonstrate our approach on a variety of input Models obtained from different sources, such as interactive Modelling systems, reconstructed scans of real trees and developmental Models.
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Inverse design of urban Procedural Models
ACM Transactions on Graphics, 2012Co-Authors: Carlos A. Vanegas, Daniel G. Aliaga, Ignacio Garcia-dorado, Bedrich Benes, Paul WaddellAbstract:We propose a framework that enables adding intuitive high level control to an existing urban Procedural Model. In particular, we pro- vide a mechanism to interactively edit urban Models, a task which is important to stakeholders in gaming, urban planning, mapping, and navigation services. Procedural Modeling allows a quick creation of large complex 3D Models, but controlling the output is a well- known open problem. Thus, while forward Procedural Modeling has thrived, in this paper we add to the arsenal an inverse Modeling tool. Users, unaware of the rules of the underlying urban Procedural Model, can alternatively specify arbitrary target indicators to con- trol the Modeling process. The system itself will discover how to alter the parameters of the urban Procedural Model so as to produce the desired 3D output. We label this process inverse design.
Sebastjan Zorzut - One of the best experts on this subject based on the ideXlab platform.
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Use of a Procedural Model in the design of production control for a polymerization plant
The International Journal of Advanced Manufacturing Technology, 2009Co-Authors: Sebastjan Zorzut, Dejan Gradišar, Vladimir Jovan, Gašper MušičAbstract:Process manufacturing has a number of characteristics that make it different from other types of manufacturing. These characteristics are reflected in the design of process production control. This article addresses some features of process manufacturing that have to be taken into account during the design of a production control system in the process industries and gives an example of the design of a process production control system based on production performance indicators. The description of a Model of a case study polymerization production plant is presented. Based on this Model, a control structure framework is proposed, which makes it possible to automate part of the manager’s work. In this study, the Model-based controller is introduced to the control structure.
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Production Control of a Polymerization Plant using a Reduced Set of Control Variables
2008 IEEE Conference on Robotics Automation and Mechatronics, 2008Co-Authors: Vladimir Jovan, Dejan Gradišar, Sebastjan ZorzutAbstract:The specifics of process manufacturing have a great influence on production management, and the focus of process-production control is to maintain stable and cost-effective production within given constraints. The synthesis of production-control structures is thus recognized as one of the most important design problems in process-production management. This paper proposes a closed-loop control structure with the utilization of production-performance indicators (pPIs) as a possible solution to this problem. pPIs represent the translation of operating objectives, such as the minimization of production costs, to a reduced set of control variables that can then be used in a feedback control. The idea of production-feedback control using production PIs as referenced, controlled variables was implemented on a Procedural Model of a production process for a polymerization plant. Some preliminary results demonstrate the usefulness of the proposed methodology.
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Use of Key Performance Indicators in Production Management
2006 IEEE Conference on Cybernetics and Intelligent Systems, 2006Co-Authors: Vladimir Jovan, Sebastjan ZorzutAbstract:Improving production performance requires the definition of global production objectives with a proper implementation strategy and suitable closed-loop control for their achievement. Closed-loop control structures for simple systems like temperature or velocity control are well defined, but a synthesis of plant-wide control structures is still recognised as the most crucial production management design problem in process industries. One vital issue to be resolved is how to translate implicit operating objectives, such as the minimisation of production costs into a set of measurable variables that can be then used in a feedback-control. A promising solution is the use of the key performance indicator (KPI) approach. To verify the idea of production feedback control using production KPIs as referenced controlled variables, a Procedural Model of a production process for a polymerisation plant has been developed. The Model has been used during a number of simulation runs performed with the aim of developing and verifying the idea of KPI-based production control
Paul Waddell - One of the best experts on this subject based on the ideXlab platform.
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Inverse design of urban Procedural Models
ACM Transactions on Graphics, 2012Co-Authors: Carlos A. Vanegas, Daniel G. Aliaga, Ignacio Garcia-dorado, Bedrich Benes, Paul WaddellAbstract:We propose a framework that enables adding intuitive high level control to an existing urban Procedural Model. In particular, we pro- vide a mechanism to interactively edit urban Models, a task which is important to stakeholders in gaming, urban planning, mapping, and navigation services. Procedural Modeling allows a quick creation of large complex 3D Models, but controlling the output is a well- known open problem. Thus, while forward Procedural Modeling has thrived, in this paper we add to the arsenal an inverse Modeling tool. Users, unaware of the rules of the underlying urban Procedural Model, can alternatively specify arbitrary target indicators to con- trol the Modeling process. The system itself will discover how to alter the parameters of the urban Procedural Model so as to produce the desired 3D output. We label this process inverse design.
Michael T. Ullman - One of the best experts on this subject based on the ideXlab platform.
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The declarative/Procedural Model of lexicon and grammar.
Journal of Psycholinguistic Research, 2020Co-Authors: Michael T. UllmanAbstract:Our use of language depends upon two capacities: a mental lexicon of memorized words and a mental grammar of rules that underlie the sequential and hierarchical composition of lexical forms into predictably structured larger words, phrases, and sentences. The declarative/Procedural Model posits that the lexicon/grammar distinction in language is tied to the distinction between two well-studied brain memory systems. On this view, the memorization and use of at least simple words (those with noncompositional, that is, arbitrary form-meaning pairings) depends upon an associative memory of distributed representations that is subserved by temporal-lobe circuits previously implicated in the learning and use of fact and event knowledge. This “declarative memory” system appears to be specialized for learning arbitrarily related information (i.e., for associative binding). In contrast, the acquisition and use of grammatical rules that underlie symbol manipulation is subserved by frontal/basal-ganglia circuits previously implicated in the implicit (nonconscious) learning and expression of motor and cognitive “skills” and “habits” (e.g., from simple motor acts to skilled game playing). This “Procedural” system may be specialized for computing sequences. This novel view of lexicon and grammar offers an alternative to the two main competing theoretical frameworks. It shares the perspective of traditional dual-mechanism theories in positing that the mental lexicon and a symbol-manipulating mental grammar are subserved by distinct computational components that may be linked to distinct brain structures. However, it diverges from these theories where they assume components dedicated to each of the two language capacities (that is, domain-specific) and in their common assumption that lexical memory is a rote list of items. Conversely, while it shares with single-mechanism theories the perspective that the two capacities are subserved by domain-independent computational mechanisms, it diverges from them where they link both capacities to a single associative memory system with broad anatomic distribution. The declarative/Procedural Model, but neither traditional dual- nor single-mechanism Models, predicts double dissociations between lexicon and grammar, with associations among associative memory properties, memorized words and facts, and temporal-lobe structures, and among symbol-manipulation properties, grammatical rule products, motor skills, and frontal/basal-ganglia structures. In order to contrast lexicon and grammar while holding other factors constant, we have focused our investigations of the declarative/Procedural Model on morphologically complex word forms. Morphological transformations that are (largely) unproductive (e.g., in go—went, solemn—solemnity) are hypothesized to depend upon declarative memory. These have been contrasted with morphological transformations that are fully productive (e.g., in walk—walked, happy—happiness), whose computation is posited to be solely dependent upon grammatical rules subserved by the Procedural system. Here evidence is presented from studies that use a range of psycholinguistic and neurolinguistic approaches with children and adults. It is argued that converging evidence from these studies supports the declarative/Procedural Model of lexicon and grammar.
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implications of the declarative Procedural Model for improving second language learning the role of memory enhancement techniques
Second Language Research, 2018Co-Authors: Michael T. Ullman, Jarrett LovelettAbstract:The declarative/Procedural (DP) Model posits that the learning, storage, and use of language critically depend on two learning and memory systems in the brain: declarative memory and Procedural memory. Thus, on the basis of independent research on the memory systems, the Model can generate specific and often novel predictions for language. Till now most such predictions and ensuing empirical work have been motivated by research on the neurocognition of the two memory systems. However, there is also a large literature on techniques that enhance learning and memory. The DP Model provides a theoretical framework for predicting which techniques should extend to language learning, and in what circumstances they should apply. In order to lay the neurocognitive groundwork for these predictions, here we first summarize the neurocognitive fundamentals of the two memory systems and briefly lay out the resulting claims of the DP Model for both first and second language. We then provide an overview of learning and me...
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the declarative Procedural Model a neurobiological Model of language learning knowledge and use
2016Co-Authors: Michael T. UllmanAbstract:Most research on the neurobiology of language focuses on language alone. However, new biological functions commonly make use of previously existing mechanisms. Thus, language likely relies on previously existing neurobiological substrates, whether or not these have become further specialized for language. The declarative/Procedural Model posits that language learning, storage, and use depend heavily on declarative and Procedural memory. After all, most, if not all, of language must be learned, and these are the two most important learning and memory systems in the brain. Crucially, both systems are well-studied at many levels in humans and animals, leading to numerous independent predictions about language. Here, I first present background on the neurobiology of the two systems, then lay out ensuing predictions for language, and finally examine evidence testing these predictions. The evidence suggests that language indeed depends on declarative and Procedural memory, moreover in interesting and informative ways that advance our understanding of the neurobiology of language.
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chapter 76 the declarative Procedural Model a neurobiological Model of language learning knowledge and use
Neurobiology of Language, 2016Co-Authors: Michael T. UllmanAbstract:Most research on the neurobiology of language focuses on language alone. However, new biological functions commonly make use of previously existing mechanisms. Thus, language likely relies on previously existing neurobiological substrates, whether or not these have become further specialized for language. The declarative/Procedural Model posits that language learning, storage, and use depend heavily on declarative and Procedural memory. After all, most, if not all, of language must be learned, and these are the two most important learning and memory systems in the brain. Crucially, both systems are well-studied at many levels in humans and animals, leading to numerous independent predictions about language. Here, I first present background on the neurobiology of the two systems, then lay out ensuing predictions for language, and finally examine evidence testing these predictions. The evidence suggests that language indeed depends on declarative and Procedural memory, moreover in interesting and informative ways that advance our understanding of the neurobiology of language.
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the declarative Procedural Model and the shallow structure hypothesis
Applied Psycholinguistics, 2006Co-Authors: Michael T. UllmanAbstract:Clahsen and Felser (CF) have written a beautiful and important paper. I applaud their integrative empirical approach, and believe that their theoretical account is largely correct, if not in some of its specific claims, at least in its broader assumptions. CF directly compare their shallow structure hypothesis (SSH) with a Model that my colleagues and I have proposed for aspects of the neurocognition of first and second language: the “declarative/Procedural” (DP) Model. Although some of CF's discussion accurately depicts the DP Model and its relation to the data, they also make a few critical errors.Here, I first summarize the DP Model in both first language (L1) and adult-learned second language (L2), in order to be able to contrast it with the SSH, and then address the relevant problems in CF. For further details on the DP Model and L1, see Ullman (2001a, 2001c, 2004) and Ullman et al. (1997). For the Model as it applies to L2, see Ullman (2001b, 2005).
Daniel G. Aliaga - One of the best experts on this subject based on the ideXlab platform.
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Interactive sketching of urban Procedural Models
ACM Transactions on Graphics, 2016Co-Authors: Nishida, Daniel G. Aliaga, Ignacio Garcia-dorado, Bedrich Benes, Adrien BousseauAbstract:3D Modeling remains a notoriously difficult task for novices despite significant research effort to provide intuitive and automated systems. We tackle this problem by combining the strengths of two popular domains: sketch-based Modeling and Procedural Modeling. On the one hand, sketch-based Modeling exploits our ability to draw but requires detailed, unambiguous drawings to achieve complex Models. On the other hand, Procedural Modeling automates the creation of precise and detailed geometry but requires the tedious definition and parameterization of Procedural Models. Our system uses a collection of simple Procedural grammars, called snippets, as building blocks to turn sketches into realistic 3D Models. We use a machine learning approach to solve the inverse problem of finding the Procedural Model that best explains a user sketch. We use non-photorealistic rendering to generate artificial data for training convolutional neural networks capable of quickly recognizing the Procedural rule intended by a sketch and estimating its parameters. We integrate our algorithm in a coarse-to-fine urban Modeling system that allows users to create rich buildings by successively sketching the building mass, roof, facades, windows, and ornaments. A user study shows that by using our approach non-expert users can generate complex buildings in just a few minutes.
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Proceduralization for Editing 3D Architectural Models
2016 Fourth International Conference on 3D Vision (3DV), 2016Co-Authors: İlke Demir, Daniel G. Aliaga, Bedrich BenesAbstract:Inverse Procedural Modeling discovers a Procedural representation of an existing geometric Model and the discovered Procedural Model then supports synthesizing new similar Models. We introduce an automatic approach that generates a compact, efficient, and re-usable Procedural representation of a polygonal 3D architectural Model. This representation is then used for structure-aware editing and synthesis of new geometric Models that resemble the original. Our framework captures the pattern hierarchy of the input Model into a split tree data representation. A context-free split grammar, supporting a hierarchical nesting of Procedural rules, is extracted from the tree, which establishes the base of our interactive Procedural editing engine. We show the application of our approach to a variety of architectural structures obtained by Procedurally editing web-sourced Models. The grammar generation takes a few minutes even for the most complex input and synthesis is fully interactive for buildings composed of up to 200k polygons.
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Inverse design of urban Procedural Models
ACM Transactions on Graphics, 2012Co-Authors: Carlos A. Vanegas, Daniel G. Aliaga, Ignacio Garcia-dorado, Bedrich Benes, Paul WaddellAbstract:We propose a framework that enables adding intuitive high level control to an existing urban Procedural Model. In particular, we pro- vide a mechanism to interactively edit urban Models, a task which is important to stakeholders in gaming, urban planning, mapping, and navigation services. Procedural Modeling allows a quick creation of large complex 3D Models, but controlling the output is a well- known open problem. Thus, while forward Procedural Modeling has thrived, in this paper we add to the arsenal an inverse Modeling tool. Users, unaware of the rules of the underlying urban Procedural Model, can alternatively specify arbitrary target indicators to con- trol the Modeling process. The system itself will discover how to alter the parameters of the urban Procedural Model so as to produce the desired 3D output. We label this process inverse design.