Polygonal-functional hybrids for computer animation and games

We present the use of mapping functions to automatically generate levels of detail with known error bounds for polygonal models. We develop a piece-wise linear mapping function for each simplification operation and use this function to measure deviation of the new surface from both the previous level of detail and from the original surface. In addition, we use the mapping function to compute appropriate texture coordinates if the original map has texture coordinates at its vertices. Our overall algorithm uses edge collapse operations. We present rigorous procedures for the generation of local planar projections as well as for the selection of a new vertex position for the edge collapse operation. As compared to earlier methods, our algorithm is able to compute tight error bounds on surface deviation and produce an entire continuum of levels of detail with mappings between them. We demonstrate the effectiveness of our algorithm on several models: a Ford Bronco consisting of over 300 parts and 70,000 triangles, a textured lion model consisting of 49 parts and 86,000 triangles, and a textured, wrinkled torus consisting of 79,000 triangles.

This paper presents a new distributed method for virtual Earth terrain tessellation on a graphics processing unit (GPU) for space simulator complexes. The method operates in real time in multi-object virtual scenes comprising up to two million polygons. A polygonal terrain model is constructed using triangle patches of different levels of detail on graphics cards with programmable tessellation. Patches of the same level of detail are calculated entirely on the GPU, in parallel and independently, by using a developed shader program written in the OpenGL Shading Language (GLSL). This paper also describes a patch extraction algorithm for visible Earth surface rendering and an algorithm for correcting the barycentric coordinates of tessellated patch vertices that allows triangles in the terrain model to be docked without geometric discontinuities. Based on the distributed methods and algorithms developed, a program complex for virtual Earth surface visualization was created and successfully tested. The proposed solution can also be employed in virtual environment systems, virtual labs, educational geo-applications, etc.

Virtual reality applications such as computer games form a large portion of the computing industry. The increasing expectations for immersive and interactive entertainment require fast graphics rendering with a lot of details and high-fidelity physics simulation. Interference and collision detection between general polygonal models, including all those tasks in the simulated motion of solids which cannot penetrate one another, has been widely explored. The most recent works have been focused on increasing the number of collision queries per second to an interactive rate, assuming that the computing resources such as memory, CPU capacity, and network bandwidth are sufficient all the time. However, the performance of a collision detection algorithm may vary in real environments where the available computing resources are not sufficient or are dynamic at runtime. Such an unstable performance directly affects the interactive rate of many applications, which is not acceptable. This drawback has been noticed extensively by practitioners. Little research work has been introduced to systematically solve this problem. One way out of this problem is to use a technique to dynamically adjust the cost of the collision detection (CD) task according to the measurements of available resources. In this dissertation, a solution to the problem is proposed. The problem is analyzed under three different physical environments: single low end computer, clustered multiple-machine setting, and distributed environment. An extensive comparative study of several methods is done in the context of polygonal models. A new approach, "multi-resolution collision detection", is proposed. It performs time-critical and exact interference detection on continuous level of detail (LOD) representations of arbitrary triangle meshes undergoing rigid body motion. The goal of this work is to extend the bounding volume hierarchy (BVH) based collision detection approach from static to dynamic in order to adapt the cost of collision detection to the available resource in either centralized or distributed environments. Several adaptive mesh refinement criteria based on viewing distance, application context, and movement velocity are proposed. Global and local mesh refinement algorithms and a BVH CD algorithm are introduced. They are computationally simple and achieve reliable real-time performance. The complexity of the proposed algorithms is analyzed and proved. Measurements are taken to compare with the analytical results and strong agreements are achieved. The major application areas considered are distributed virtual environments (DVEs) and interactive haptic applications.

Polygonal models are ubiquitous in computer graphics but their real time manipulation and rendering especially in interactive application environments have become a threat because of their huge sizes and complexity. A whole family of automatic algorithms emerged during the last decade to help out this problem, but they reduce the complexity of the models uniformly without caring about semantic importance of localized parts of a mesh. Only a few algorithms deal with adaptive simplification of polygonal models. We propose a new model for user-driven simplification exploiting the simplification hierarchy and hypertriangulation model [P. Cignoni et al.] that lends a user the most of the functionalities of existing adaptive simplification algorithms in one place and is quite simple to implement. The proposed new underlying data structures are compact and support real time navigation across continuous LODs of a model; any desirable LOD can be extracted efficiently and can further be fine-tuned. The proposed model for adaptive simplification supports two key operations for selective refinement and selective simplification; their effect has been shown on various polygonal models. Comparison with related work shows that the proposed model provides combined environment at reduced overhead of memory space usage and faster running times.

There are many applications, such as pilot training, mission rehearsal, and hardware-in-the-loop simulation, which require the generation of realistic images of terrain and man-made objects in real-time. One well-known approach to meeting this requirement is to drape photo-texture over a planar polygon model of the terrain. The real time system then computes, for each pixel of the output image, the address in a texture map based on the intersection of the line-of-sight vector with the terrain model. High quality image generation requires that the terrain be modeled with a fine mesh of polygons while hardware costs limit the number of polygons which may be displayed for each scene. The trade-off between these conflicting requirements must be made in real-time because it depends on the changing position and orientation of the pilot's eye point or simulated sensor. The traditional approach is to develop a data base consisting of multiple levels of detail (LOD), and then selecting for display LOD's as a function of range. This approach could lead to both anomalies in the displayed scene and inefficient use of resources. In this paper, a new approach has been developed in which the terrain is modeled with a set of polygons and organized as a graph with each node corresponding to a polygon. This graph is pruned to select the optimum set of nodes for each eye-point position. The novelty of the proposed graph pruning lies in the coherence suggested in the selection of terrain LODs and texture LODs. The error in terrain representation is expressed in terms of the error in the texture pixels. This allows different error criteria to be used for different applications. Texas 76019 As the point of view moves, the visibility of some nodes drops below the limit of perception and may be deleted while new nodes must be added in regions near the eye point. Our pervious work has been generalized to include the case where the refinements of the polygonization are not simply nested and the graph is not a simple tree. This generalization prevents the occurrence of gaps in terrain representation.

The use of appearance and shape priors in image segmentation is known to improve accuracy; however, existing techniques have several drawbacks. For instance, most active shape and appearance models require landmark points and assume unimodal shape and appearance distributions, and the level set representation does not support construction of local priors. In this paper, we present novel appearance and shape models for image segmentation based on a differentiable implicit parametric shape representation called a disjunctive normal shape model (DNSM). The DNSM is formed by the disjunction of polytopes, which themselves are formed by the conjunctions of half-spaces. The DNSM's parametric nature allows the use of powerful local prior statistics, and its implicit nature removes the need to use landmarks and easily handles topological changes. In a Bayesian inference framework, we model arbitrary shape and appearance distributions using nonparametric density estimations, at any local scale. The proposed local shape prior results in accurate segmentation even when very few training shapes are available, because the method generates a rich set of shape variations by locally combining training samples. We demonstrate the performance of the framework by applying it to both 2-D and 3-D data sets with emphasis on biomedical image segmentation applications.

This thesis contains a set of contributions that focuses on challenges in visualization of polygon models of trees, in particular models of tree stems and branches. These challenges cover a wide range of the visualization research field, including generation of polygon models of trees, hardware accelerated visualization and animation of trees from parametric systems, and surface modelling and tessellation for tree stems. To generate polygon models of trees, an existing approach for automatically generating polygon models of branching vascular transportation systems, typically blood vessels, is extended to handle tree stems. The approach allowed for automation of the generation process, while maintaining smoothness at branching areas. The approach is used to generate polygon models of trees. For hardware accelerated visualization and animation of trees from parametric systems, methods for visualization of trees described by parametric descriptions are adapted and extended to run on dedicated graphic processing hardware. To allow for animation of trees visualized in such a manner, an animation process that is hardware accelerated is developed using knowledge gained from work on hardware acceleration approaches in the field of image processing. For surface modelling and tessellation for visualization of trees, concepts, ideas and early work are presented. The basic concept is that by working with a coarse polygon model of a tree during animation (or by generating a coarse polygon model of a tree after animation is done); one can tessellate this coarse model in hardware in real-time to a much higher degree then earlier approaches. This will then enable one to visualize trees stems of a higher Level of Detail (LOD) and at higher speeds than were previously achievable. Although the contributions in this thesis cover a wide range of challenges from the visualization research field, the main focus has been on generation, animation and visualization of tree stems and branches for use in real-time applications. Especially the concept of hardware acceleration has become more of a focus, as graphic processing hardware has become more and more powerful both in speed and especially in functionality. The contributions will hopefully help in future development of even better methods for visualizing trees and plants.

Large-scale three-dimensional spatial data has gained increasing attention with the development of self-driving, mineral exploration, CAD, and human atlases. Such 3D objects are often represented with a polygonal model at high resolution to preserve accuracy. This poses major challenges for 3D data management and spatial queries due to the massive amounts of 3D objects, e.g., trillions of 3D cells, and the high complexity of 3D geometric computation. Traditional spatial querying methods in the Filter-Refine paradigm have a major focus on indexing-based filtering using approximations like minimal bounding boxes and largely neglect the heavy computation in the refinement step at the intra-geometry level, which often dominates the cost of query processing. In this paper, we introduce 3DPro, a system that supports efficient spatial queries for complex 3D objects. 3DPro uses progressive compression of 3D objects preserving multiple levels of details, which significantly reduces the size of the objects and has the data fit into memory. Through a novel Filter-Progressive-Refine paradigm, 3DPro can have query results returned early whenever possible to minimize decompression and geometric computations of 3D objects in higher resolution representations. Our experiments demonstrate that 3DPro out-performs the state-of-the-art 3D data processing techniques by up to an order of magnitude for typical spatial queries.

У статті проаналізовано особливості вибору рівня щільності полігональноїмоделі для тривимірної комп’ютерної гри. Описано поняття триангуляції, щільностіполігональної сітки, рівня деталізації. Обґрунтовано актуальність налаштування щільностіполігональн

We study how mixed reality (MR) telepresence can enhance long-distance human interaction and how altering 3D representations of a remote person can be used to modulate stress and anxiety during social interactions. To do so, we developed an MR telepresence system employing commodity depth sensors and Microsoft’s Hololens. A textured, polygonal 3D model of a person was reconstructed in real time and transmitted over network for rendering in remote location using HoloLens. In this study, we used mock job interview paradigm to induce stress in human–subjects interacting with an interviewer presented as an MR hologram. Participants were exposed to three different types of real-time reconstructed virtual holograms of the interviewer, a natural-sized 3D reconstruction (NR), a miniature 3D reconstruction (SR) and a 2D-display representation (LCD). Participants reported their subjective experience through questionnaires, while their biophysical responses were recorded. We found that the size of 3D representation of a remote interviewer had a significant effect on participants’ stress levels and their sense of presence. The questionnaire data showed that NR condition induced more stress and presence than SR condition and was significantly different from LCD condition. We also found consistent patterns in the biophysical data.

Recently more researches on tangible objects have been conducted that enhance the intuitive polygonal or surface modelling of designers in digital and physical worlds. However, a few researches have been done that augment the digital solid modelling with tangible objects. In this paper, we present the Augmented Solid Modeller (ASoM) which helps designers create more complex shapes by a combination of Boolean operations between a different type of 3D-printed tangible objects, which is different from the conventional single shape type bottom-up modelling approaches. When multiple objects intersect each other at a given position and angle, the interference or removed shape is often unexpected for designers. Also, as 3D-printed objects are used for designers only to configure and discuss the shape of final digital 3D model in existing CAAD, ASoM changes the role of 3D-printed objects from the replicas to reusable tools for other modelling opportunities. We offered ASoM to students majoring or interested in CAAD and interviewed them to get comments. Since the speed and precision of 3D-printing will achieve immediate improvement, ASoM is a pioneer in developing cutting-edge approach for designers to model both in digital and physical worlds.

Leveraging virtualization technology, Mobile Edge Computing (MEC) deploys multiple services with different execution time requirements running as isolated processes. For instance, both real-time (RT) and non-RT applications may be (are) running on the same infrastructure using containerized virtualization. Nevertheless, sharing resources (e.g., CPU) with collocated workloads could impact the RT performance of RT applications. This paper presents PRINCIPIA, a dynamic CPU and CPU-shares allocation mechanism that opportunistically enables non-RT applications to run on underutilized CPUs while providing RT guarantees to RT applications. By monitoring MEC’s system metrics like processor’s CPU utilization and container’s CPU usage, PRINCIPIA dynamically allocates both CPU and CPU-shares to containers running non-RT applications aiming at opportunistically exploiting underutilized CPUs by containers running RT applications. We evaluate PRINCIPIA on a small-scale MEC server which uses containerized virtualization along with Linux RT Kernel to deploy both RT and non-RT applications. Our findings show that PRINCIPIA mitigates the impact on the RT performance of RT applications providing bounded processing latency in comparison with the default host Kernel scheduler.

Real-time simulation of viscoelastic tissue behavior with physics-guided deep learning.

In order to monitor the OSPF (Open Shortest Path First) large-scale autonomous system in real time, for the shortcomings of current topology discovery methods based on OSPF protocol, firstly a hierarchical modelling method of OSPF large-scale autonomous system is proposed, which describes the autonomous system quantitatively. Secondly, a topology generation algorithm based on the link state database and an autonomous system model comparison algorithm are put forward in this paper. Finally, the experiment of monitoring the autonomous system in the actual network is carried out. The link state database is collected on any router in each OSPF area. The experiments show that the model and algorithm can be used to obtain the network topology map completely and accurately without the extra network burden, and to monitor the changes of network topology in real time. The model and algorithm proposed in this paper are helpful to realize the topology generation and monitoring of the large-scale autonomous system.

Cyber-physical systems are realized as those systems where the computation, communication and physical processes interact with each other (e.g., robotic systems, automotives, etc). A large class of cyber-physical systems are associated with strict timeliness requirements. They are known as ‘real-time systems’ (e.g., smart grids, avionics, etc). Industrial control systems (ICS) are real-time systems that consist of several closed-loop controls. The main components of a control loop are — a physical plant, sensors, actuators and a controller. The sensors transmit the measurement data to the controller that generates appropriate control signals to actuate the physical plant. Large-scale wireless sensor actuator networks form the main communication framework among the network devices in ICS. Most of the communications between each of these devices are periodic real-time flows with hard deadlines. To ensure reliability, the communication in these systems are time-division multiple access (TDMA) based. Dedicated network resources (time-slots and frequencies) are allocated to these devices in advance and the communication schedule is pre-computed to satisfy the hard deadlines of the real-time flows. The same schedule is repeated over time which makes the schedule predictable in nature. However, a malicious attacker can exploit this predictable time-slots in the schedules to launch timing attacks. Since these applications are time-critical, timing attacks can completely undermine the system performance leading the system to an unsafe state. Schedule randomization is a popular defense mechanism to mitigate timing attacks. Although a few works exist in the literature that use schedule randomization as a countermeasure against timing attacks in real-time uniprocessor systems, none of them are applicable for real-time wireless networks. Schedule randomization as a countermeasure against timing attacks in real-time wireless networks remained largely unexplored. With this objective in focus, this thesis addresses some schedule randomization techniques to mitigate timing attacks in real-time wireless networks. Among the existing wireless network protocols that are in use, the WirelessHART is the most suitable and widely adopted protocol in ICS. A WirelessHART protocol supports centralized architecture, TDMA based communication, multiple channels, etc. All of these characteristics of a WirelessHART network facilitate reliable and predictable communication with real-time flow guarantees in ICS. However, the predictable communication exposes the system to timing attacks, such as selective jamming attacks. Selective jamming attacks are stealthy attacks, however, it can lead the system to an unstable state and can disrupt the safety of the system. As a countermeasure against such attack in WirelessHART network, we propose a centralized schedule randomization technique that randomizes the time-slots and channels in the schedule over every hyperperiod (least common multiple of the periods of the real-time flows) without violating the hard deadlines of the real-time flows, while still satisfying the feasibility constraints of a schedule in a WirelessHART network. The centralized technique generates the schedules offline and distributes the schedules online, hence, cannot support any change in topology in the network. Further, this technique has energy overheads in distributing the schedules to all the network devices at runtime. Hence, we propose a distributed online schedule randomization technique that can generate random feasible schedules at runtime in each network device without affecting the closed-loop control stability. To increase the extent of randomization of time-slots in the schedules, this online distributed technique adopts a period adaptation strategy that can adjust the transmission periods of the real-time flows at runtime depending on the stability of the closed-loop controls. To support an ever-growing number of devices and dense connectivity, the fifth generation (5G) cellular networks is expected to serve as the main communication standard in the future wireless sensor networks. Among the different service categories supported by 5G, the ultra-reliable low-latency communication (URLLC) is mostly suitable for time-critical applications such as the ICS. The communication in 5G is organized into slots over multiple frequencies. To satisfy the hard deadlines of the URLLC flows in ICS, a part of the resources (slots and frequencies) in 5G are reserved for URLLC traffic and the same schedule is repeated over time. The repetition of the same schedule over time makes the slots in the schedules predictable. This, in turn, makes the 5G networks vulnerable to timing attacks. However, the proposed schedule randomization techniques for WirelessHART networks are not applicable for dynamic networks like 5G where the number of flows and the amount of available network resources for URLLC flows vary at runtime. Moreover, the feasibility of the real-time flows need to be guaranteed at runtime. Hence, we propose an online schedule randomization technique that randomizes the slots and the frequencies of the periodic URLLC flows while guaranteeing the feasibility of the flows at runtime.