39-Issue 1

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https://diglib.eg.org/handle/10.2312/2632880

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Detection and Synthesis of Full‐Body Environment Interactions for Virtual Humans
(© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020) Juarez‐Perez, A.; Kallmann, M.; Benes, Bedrich and Hauser, Helwig
We present a new methodology for enabling virtual humans to autonomously detect and perform complex full‐body interactions with their environments. Given a parameterized walking controller and a set of motion‐captured example interactions, our method is able to detect when interactions can occur and to coordinate the detected upper‐body interaction with the walking controller in order to achieve full‐body mobile interactions in similar situations. Our approach is based on learning spatial coordination features from the example motions and on associating body‐environment proximity information to the body configurations of each performed action. Body configurations become the input to a regression system, which in turn is able to generate new interactions for different situations in similar environments. The regression model is capable of selecting, encoding and replicating key spatial strategies with respect to body coordination and management of environment constraints as well as determining the correct moment in time and space for starting an interaction. As a result, we obtain an interactive controller able to detect and synthesize coordinated full‐body motions for a variety of complex interactions requiring body mobility. Our results achieve complex interactions, such as opening doors and drawing in a wide whiteboard. The presented approach introduces the concept of learning interaction coordination models that can be applied on top of any given walking controller. The obtained method is simple and flexible, it handles the detection of possible interactions and is suitable for real‐time applications.
Microstructure Control in 3D Printing with Digital Light Processing
(© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020) Luongo, A.; Falster, V.; Doest, M. B.; Ribo, M. M.; Eiriksson, E. R.; Pedersen, D. B.; Frisvad, J. R.; Benes, Bedrich and Hauser, Helwig
Digital light processing stereolithography is a promising technique for 3D printing. However, it offers little control over the surface appearance of the printed object. The printing process is typically layered, which leads to aliasing artefacts that affect surface appearance. An antialiasing option is to use greyscale pixel values in the layer images that we supply to the printer. This enables a kind of subvoxel growth control. We explore this concept and use it for editing surface microstructure. In other words, we modify the surface appearance of a printed object by applying a greyscale pattern to the surface voxels before sending the cross‐sectional layer images to the printer. We find that a smooth noise function is an excellent tool for varying surface roughness and for breaking the regularities that lead to aliasing. Conversely, we also present examples that introduce regularities to produce controlled anisotropic surface appearance. Our hope is that subvoxel growth control in stereolithography can lead 3D printing towards customizable surface appearance. The printing process adds what we call ground noise to the printed result. We suggest a way of modelling this ground noise to provide users with a tool for estimating a printer's ability to control surface reflectance.
Paradigm
(© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020) Benes, Bedrich and Hauser, Helwig
Gaussian Product Sampling for Rendering Layered Materials
(© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020) Xia, Mengqi (Mandy); Walter, Bruce; Hery, Christophe; Marschner, Steve; Benes, Bedrich and Hauser, Helwig
To increase diversity and realism, surface bidirectional scattering distribution functions (BSDFs) are often modelled as consisting of multiple layers, but accurately evaluating layered BSDFs while accounting for all light transport paths is a challenging problem. Recently, Guo . [GHZ18] proposed an accurate and general position‐free Monte Carlo method, but this method introduces variance that leads to longer render time compared to non‐stochastic layered models. We improve the previous work by presenting two new sampling strategies, and . Our new methods better take advantage of the layered structure and reduce variance compared to the conventional approach of sequentially sampling one BSDF at a time. Our strategy importance samples the product of two BSDFs from a pair of adjacent layers. We further generalize this to , which importance samples the product of a chain of three or more BSDFs. In order to compute these products, we developed a new approximate Gaussian representation of individual layer BSDFs. This representation incorporates spatially varying material properties as parameters so that our techniques can support an arbitrary number of textured layers. Compared to previous Monte Carlo layering approaches, our results demonstrate substantial variance reduction in rendering isotropic layered surfaces.
Graph‐Based Transfer Function for Volume Rendering
(© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020) Sharma, O.; Arora, T.; Khattar, A.; Benes, Bedrich and Hauser, Helwig
A good transfer function in volume rendering requires careful consideration of the materials present in a volume. A manual creation is tedious and prone to errors. Furthermore, the user interaction to design a higher dimensional transfer function gets complicated. In this work, we present a graph‐based approach to design a transfer function that takes volumetric structures into account. Our novel contribution is in proposing an algorithm for robust deduction of a material graph from a set of disconnected edges. We incorporate stable graph creation under varying noise levels in the volume. We show that the deduced material graph can be used to automatically create a transfer function using the occlusion spectrum of the input volume. Since we compute material topology of the objects, an enhanced rendering is possible with our method. This also allows us to selectively render objects and depict adjacent materials in a volume. Our method considerably reduces manual effort required in designing a transfer function and provides an easy interface for interaction with the volume.
Compressed Neighbour Lists for SPH
(© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020) Band, Stefan; Gissler, Christoph; Teschner, Matthias; Benes, Bedrich and Hauser, Helwig
We propose a novel compression scheme to store neighbour lists for iterative solvers that employ Smoothed Particle Hydrodynamics (SPH). The compression scheme is inspired by Stream VByte, but uses a non‐linear mapping from data to data bytes, yielding memory savings of up to 87%. It is part of a novel variant of the Cell‐Linked‐List (CLL) concept that is inspired by compact hashing with an improved processing of the cell‐particle relations. We show that the resulting neighbour search outperforms compact hashing in terms of speed and memory consumption. Divergence‐Free SPH (DFSPH) scenarios with up to 1.3 billion SPH particles can be processed on a 24‐core PC using 172 GB of memory. Scenes with more than 7 billion SPH particles can be processed in a Message Passing Interface (MPI) environment with 112 cores and 880 GB of RAM. The neighbour search is also useful for interactive applications. A DFSPH simulation step for up to 0.2 million particles can be computed in less than 40 ms on a 12‐core PC.
Synthesizing Character Animation with Smoothly Decomposed Motion Layers
(© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020) Eom, Haegwang; Choi, Byungkuk; Cho, Kyungmin; Jung, Sunjin; Hong, Seokpyo; Noh, Junyong; Benes, Bedrich and Hauser, Helwig
The processing of captured motion is an essential task for undertaking the synthesis of high‐quality character animation. The motion decomposition techniques investigated in prior work extract meaningful motion primitives that help to facilitate this process. Carefully selected motion primitives can play a major role in various motion‐synthesis tasks, such as interpolation, blending, warping, editing or the generation of new motions. Unfortunately, for a complex character motion, finding generic motion primitives by decomposition is an intractable problem due to the compound nature of the behaviours of such characters. Additionally, decomposed motion primitives tend to be too limited for the chosen model to cover a broad range of motion‐synthesis tasks. To address these challenges, we propose a generative motion decomposition framework in which the decomposed motion primitives are applicable to a wide range of motion‐synthesis tasks. Technically, the input motion is smoothly decomposed into three motion layers. These are base‐level motion, a layer with controllable motion displacements and a layer with high‐frequency residuals. The final motion can easily be synthesized simply by changing a single user parameter that is linked to the layer of controllable motion displacements or by imposing suitable temporal correspondences to the decomposition framework. Our experiments show that this decomposition provides a great deal of flexibility in several motion synthesis scenarios: denoising, style modulation, upsampling and time warping.
Example‐Based Colourization Via Dense Encoding Pyramids
(© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020) Xiao, Chufeng; Han, Chu; Zhang, Zhuming; Qin, Jing; Wong, Tien‐Tsin; Han, Guoqiang; He, Shengfeng; Benes, Bedrich and Hauser, Helwig
We propose a novel deep example‐based image colourization method called dense encoding pyramid network. In our study, we define the colourization as a multinomial classification problem. Given a greyscale image and a reference image, the proposed network leverages large‐scale data and then predicts colours by analysing the colour distribution of the reference image. We design the network as a pyramid structure in order to exploit the inherent multi‐scale, pyramidal hierarchy of colour representations. Between two adjacent levels, we propose a hierarchical decoder–encoder filter to pass the colour distributions from the lower level to higher level in order to take both semantic information and fine details into account during the colourization process. Within the network, a novel parallel residual dense block is proposed to effectively extract the local–global context of the colour representations by widening the network. Several experiments, as well as a user study, are conducted to evaluate the performance of our network against state‐of‐the‐art colourization methods. Experimental results show that our network is able to generate colourful, semantically correct and visually pleasant colour images. In addition, unlike fully automatic colourization that produces fixed colour images, the reference image of our network is flexible; both natural images and simple colour palettes can be used to guide the colourization.
Ribbed Support Vaults for 3D Printing of Hollowed Objects
(© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020) Tricard, Thibault; Claux, Frédéric; Lefebvre, Sylvain; Benes, Bedrich and Hauser, Helwig
Additive manufacturing techniques form an object by accumulating layers of material on top of one another. Each layer has to be supported by the one below for the fabrication process to succeed. To reduce print time and material usage, especially in the context of prototyping, it is often desirable to fabricate hollow objects. This exacerbates the requirement of support between consecutive layers: standard hollowing produces surfaces in overhang that cannot be directly fabricated anymore. Therefore, these surfaces require support structures. These are similar to external supports for overhangs, with the key difference that internal supports remain invisible within the object after fabrication. A fundamental challenge is to generate structures that provide a dense support while using little material. In this paper, we propose a novel type of support inspired by rib structures. Our approach guarantees that any point in a layer is supported by a point below, within a given threshold distance. Despite providing strong guarantees for printability, our supports remain lightweight and reliable to print. We propose a greedy support generation algorithm that creates compact hierarchies of rib‐like walls. The walls are progressively eroded away and straightened, eventually merging with the interior object walls. We demonstrate our technique on a variety of models and provide performance figures in the context of fused filament fabrication 3D printing.
Muscle and Fascia Simulation with Extended Position Based Dynamics
(© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020) Romeo, M.; Monteagudo, C.; Sánchez‐Quirós, D.; Benes, Bedrich and Hauser, Helwig
Recent research on muscle and fascia simulation for visual effects relies on numerical methods such as the finite element method or finite volume method. These approaches produce realistic results, but require high computational time and are complex to set up. On the other hand, position‐based dynamics offers a fast and controllable solution to simulate surfaces and volumes, but there is no literature on how to implement constraints that could be used to realistically simulate muscles and fascia for digital creatures with this method. In this paper, we extend the current state‐of‐the‐art in Position‐Based Dynamics to efficiently compute realistic skeletal muscle and superficial fascia simulation. In particular, we embed muscle fibres in the solver by adding an anisotropic component to the distance constraints between mesh points and apply overpressure to realistically model muscle volume changes under contraction. In addition, we also define a modified distance constraint for the fascia that allows compression and enables the user to scale the constraint's original distance to gain elastic potential at rest. Finally, we propose a modification of the extended position‐based dynamics algorithm to properly compute different sets of constraints and describe other details for proper simulation of character's muscle and fascia dynamics.
Interactive Iconized Grammar‐Based Pailou Modelling
(© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020) Cai, Zhong‐Qi; Luo, Ying‐Sheng; Lai, Yu‐Chi; Chan, Chih‐Shiang; Tai, Wen‐Kai; Benes, Bedrich and Hauser, Helwig
Pailous are representative Chinese architectural works used for commemoration. However, their geometric structure and semantic construction rules are too complex for quick and intuitive modelling using traditional modelling tools. We propose an intuitive modelling system for the stylized creation of pailous for novices. Our system encapsulates structural components as icons and semantic layouts as topological graphs, using which users create and manipulate icons with topological recommendations. The interpreter automatically and immediately transforms a graph to its corresponding model using built‐in components with the proposed parametric L‐system grammars derived from architectural rules. Using this system to re‐create existing representative pailous and design imaginary ones yields results with the desired visual complexities. In comparison to Maya, a 3D modelling tool, when modelling a pailou and toukung, our system is effective and simple, and eliminates the need to remember and understand complex rules.
Reducing Affective Responses to Surgical Images and Videos Through Stylization
(© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020) Besançon, Lonni; Semmo, Amir; Biau, David; Frachet, Bruno; Pineau, Virginie; Sariali, El Hadi; Soubeyrand, Marc; Taouachi, Rabah; Isenberg, Tobias; Dragicevic, Pierre; Benes, Bedrich and Hauser, Helwig
We present the first empirical study on using colour manipulation and stylization to make surgery images/videos more palatable. While aversion to such material is natural, it limits many people's ability to satisfy their curiosity, educate themselves and make informed decisions. We selected a diverse set of image processing techniques to test them both on surgeons and lay people. While colour manipulation techniques and many artistic methods were found unusable by surgeons, edge‐preserving image smoothing yielded good results both for preserving information (as judged by surgeons) and reducing repulsiveness (as judged by lay people). We then conducted a second set of interview with surgeons to assess whether these methods could also be used on videos and derive good default parameters for information preservation. We provide extensive supplemental material at .
Memento: Localized Time‐Warping for Spatio‐Temporal Selection
(© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020) Solteszova, V.; Smit, N. N.; Stoppel, S.; Grüner, R.; Bruckner, S.; Benes, Bedrich and Hauser, Helwig
Interaction techniques for temporal data are often focused on affecting the spatial aspects of the data, for instance through the use of transfer functions, camera navigation or clipping planes. However, the temporal aspect of the data interaction is often neglected. The temporal component is either visualized as individual time steps, an animation or a static summary over the temporal domain. When dealing with streaming data, these techniques are unable to cope with the task of re‐viewing an interesting local spatio‐temporal event, while continuing to observe the rest of the feed. We propose a novel technique that allows users to interactively specify areas of interest in the spatio‐temporal domain. By employing a time‐warp function, we are able to slow down time, freeze time or even travel back in time, around spatio‐temporal events of interest. The combination of such a (pre‐defined) time‐warp function and brushing directly in the data to select regions of interest allows for a detailed review of temporally and spatially localized events, while maintaining an overview of the global spatio‐temporal data. We demonstrate the utility of our technique with several usage scenarios.
Parameterization, Feature Extraction and Binary Encoding for the Visualization of Tree‐Like Structures
(© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020) Lichtenberg, N.; Lawonn, K.; Benes, Bedrich and Hauser, Helwig
The study of vascular structures, using medical 3D models, is an active field of research. Illustrative visualizations have been applied to this domain in multiple ways. Researchers made the geometric properties of vasculature more comprehensive and augmented the surface with representations of multivariate clinical data. Techniques that head beyond the application of colour‐maps or simple shading approaches require a surface parameterization, that is, texture coordinates, in order to overcome locality. When extracting 3D models, the computation of texture coordinates on the mesh is not always part of the data processing pipeline. We combine existing techniques to a simple parameterization approach that is suitable for tree‐like structures. The parameterization is done w.r.t. to a pre‐defined source vertex. For this, we present an automatic algorithm, that detects the tree root. The parameterization is partly done in screen‐space and recomputed per frame. However, the screen‐space computation comes with positive features that are not present in object‐space approaches. We show how the resulting texture coordinates can be used for varying hatching, contour parameterization, display of decals, as additional depth cues and feature extraction. A further post‐processing step based on parameterization allows for a segmentation of the structure and visualization of its tree topology.
Broadmark: A Testing Framework for Broad‐Phase Collision Detection Algorithms
(© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020) Serpa, Ygor Rebouças; Rodrigues, Maria Andréia Formico; Benes, Bedrich and Hauser, Helwig
Research in the area of collision detection permeates most of the literature on simulations, interaction and agents planning, being commonly regarded as one of the main bottlenecks for large‐scale systems. To this day, despite its importance, most subareas of collision detection lack a common ground to test and validate solutions, reference implementations and widely accepted benchmark suites. In this paper, we delve into the broad‐phase of collision detection systems, providing both an open‐source framework, named Broadmark, to test, compare and validate algorithms, and an in‐deep analysis of the main techniques used so far to tackle the broad‐phase problem. The technical challenges of building this framework from the software and hardware perspectives are also described. Within our framework, several original and state‐of‐the‐art implementations of CPU and GPU algorithms are bundled, alongside three benchmark scenes to stress algorithms under several conditions. Furthermore, the system is designed to be easily extensible. We use our framework to bring out an extensive performance comparison among assembled solutions, detailing the current CPU and GPU state‐of‐the‐art on a common ground. We believe that Broadmark encompasses the principal insights and tools to derive and evaluate novel algorithms, thus greatly facilitating discussion about successful broad‐phase collision detection solutions.
SiamesePointNet: A Siamese Point Network Architecture for Learning 3D Shape Descriptor
(© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020) Zhou, J.; Wang, M. J.; Mao, W. D.; Gong, M. L.; Liu, X. P.; Benes, Bedrich and Hauser, Helwig
We present a novel deep learning approach to extract point‐wise descriptors directly on 3D shapes by introducing Siamese Point Networks, which contain a global shape constraint module and a feature transformation operator. Such geometric descriptor can be used in a variety of shape analysis problems such as 3D shape dense correspondence, key point matching and shape‐to‐scan matching. The descriptor is produced by a hierarchical encoder–decoder architecture that is trained to map geometrically and semantically similar points close to one another in descriptor space. Benefiting from the additional shape contrastive constraint and the hierarchical local operator, the learned descriptor is highly aware of both the global context and local context. In addition, a feature transformation operation is introduced in the end of our networks to transform the point features to a compact descriptor space. The feature transformation can make the descriptors extracted by our networks unaffected by geometric differences in shapes. Finally, an N‐tuple loss is used to train all the point descriptors on a complete 3D shape simultaneously to obtain point‐wise descriptors. The proposed Siamese Point Networks are robust to many types of perturbations such as the Gaussian noise and partial scan. In addition, we demonstrate that our approach improves state‐of‐the‐art results on the BHCP benchmark.
A Survey of Visual Analytics for Public Health
(© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020) Preim, Bernhard; Lawonn, Kai; Benes, Bedrich and Hauser, Helwig
We describe visual analytics solutions aiming to support public health professionals, and thus, preventive measures. Prevention aims at advocating behaviour and policy changes likely to improve human health. Public health strives to limit the outbreak of acute diseases as well as the reduction of chronic diseases and injuries. For this purpose, data are collected to identify trends in human health, to derive hypotheses, e.g. related to risk factors, and to get insights in the data and the underlying phenomena. Most public health data have a temporal character. Moreover, the spatial character, e.g. spatial clustering of diseases, needs to be considered for decision‐making. Visual analytics techniques involve (subspace) clustering, interaction techniques to identify relevant subpopulations, e.g. being particularly vulnerable to diseases, imputation of missing values, visual queries as well as visualization and interaction techniques for spatio‐temporal data. We describe requirements, tasks and visual analytics techniques that are widely used in public health before going into detail with respect to applications. These include outbreak surveillance and epidemiology research, e.g. cancer epidemiology. We classify the solutions based on the visual analytics techniques employed. We also discuss gaps in the current state of the art and resulting research opportunities in a research agenda to advance visual analytics support in public health.
A Cross‐Dimension Annotations Method for 3D Structural Facial Landmark Extraction
(© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020) Gong, Xun; Chen, Ping; Zhang, Zhemin; Chen, Ke; Xiang, Yue; Li, Xin; Benes, Bedrich and Hauser, Helwig
Recent methods for 2D facial landmark localization perform well on close‐to‐frontal faces, but 2D landmarks are insufficient to represent 3D structure of a facial shape. For applications that require better accuracy, such as facial motion capture and 3D shape recovery, 3DA‐2D (2D Projections of 3D Facial Annotations) is preferred. Inferring the 3D structure from a single image is an problem whose accuracy and robustness are not always guaranteed. This paper aims to solve accurate 2D facial landmark localization and the transformation between 2D and 3DA‐2D landmarks. One way to increase the accuracy is to input more precisely annotated facial images. The traditional cascaded regressions cannot effectively handle large or noisy training data sets. In this paper, we propose a Mini‐Batch Cascaded Regressions (MBCR) method that can iteratively train a robust model from a large data set. Benefiting from the incremental learning strategy and a small learning rate, MBCR is robust to noise in training data. We also propose a new Cross‐Dimension Annotations Conversion (CDAC) method to map facial landmarks from 2D to 3DA‐2D coordinates and vice versa. The experimental results showed that CDAC combined with MBCR outperforms the‐state‐of‐the‐art methods in 3DA‐2D facial landmark localization. Moreover, CDAC can run efficiently at up to 110 on a 3.4 GHz‐CPU workstation. Thus, CDAC provides a solution to transform existing 2D alignment methods into 3DA‐2D ones without slowing down the speed. Training and testing code as well as the data set can be downloaded from https://github.com/SWJTU‐3DVision/CDAC.
FARM: Functional Automatic Registration Method for 3D Human Bodies
(© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020) Marin, R.; Melzi, S.; Rodolà, E.; Castellani, U.; Benes, Bedrich and Hauser, Helwig
We introduce a new method for non‐rigid registration of 3D human shapes. Our proposed pipeline builds upon a given parametric model of the human, and makes use of the functional map representation for encoding and inferring shape maps throughout the registration process. This combination endows our method with robustness to a large variety of nuisances observed in practical settings, including non‐isometric transformations, downsampling, topological noise and occlusions; further, the pipeline can be applied invariably across different shape representations (e.g. meshes and point clouds), and in the presence of (even dramatic) missing parts such as those arising in real‐world depth sensing applications. We showcase our method on a selection of challenging tasks, demonstrating results in line with, or even surpassing, state‐of‐the‐art methods in the respective areas.
Accelerating Distributed Graphical Fluid Simulations with Micro‐partitioning
(© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020) Qu, Hang; Mashayekhi, Omid; Shah, Chinmayee; Levis, Philip; Benes, Bedrich and Hauser, Helwig
Graphical fluid simulations are CPU‐bound. Parallelizing simulations on hundreds of cores in the computing cloud would make them faster, but requires evenly balancing load across nodes. Good load balancing depends on manual decisions from experts, which are time‐consuming and error prone, or dynamic approaches that estimate and react to future load, which are non‐deterministic and hard to debug.This paper proposes Birdshot scheduling, an automatic and purely static load balancing algorithm whose performance is close to expert decisions and reactive algorithms without their difficulty or complexity. Birdshot scheduling's key insight is to leverage the high‐latency, high‐throughput, full bisection bandwidth of cloud computing nodes. Birdshot scheduling splits the simulation domain into many micro‐partitions and statically assigns them to nodes randomly. Analytical results show that randomly assigned micro‐partitions balance load with high probability. The high‐throughput network easily handles the increased data transfers from micro‐partitions, and full bisection bandwidth allows random placement with no performance penalty. Overlapping the communications and computations of different micro‐partitions masks latency.Experiments with particle‐level set, SPH, FLIP and explicit Eulerian methods show that Birdshot scheduling speeds up simulations by a factor of 2‐3, and can out‐perform reactive scheduling algorithms. Birdshot scheduling performs within 21% of state‐of‐the‐art dynamic methods that require running a second, parallel simulation. Unlike speculative algorithms, Birdshot scheduling is purely static: it requires no controller, runtime data collection, partition migration or support for these operations from the programmer.

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