Model Simplification Algorithm Research Articles

An Algorithm for Simplifying 3D Building Models with Consideration for Detailed Features and Topological Structure

To tackle problems such as the destruction of topological structures and the loss of detailed features in the simplification of 3D building models, we propose a 3D building model simplification algorithm that considers detailed features and topological structures. Based on the edge collapse algorithm, the method defines the region formed by the first-order neighboring triangles of the endpoints of the edge to be collapsed as the simplification unit. It incorporates the centroid displacement of the simplification unit, significance level, and approximate curvature of the edge as influencing factors for the collapse cost to control the edge collapse sequence and preserve model details. Additionally, considering the unique properties of 3D building models, boundary edge detection and face overlay are added as constraints to maintain the model’s topological structure. The experimental results show that the algorithm is superior to the classic QEM algorithm in terms of preserving the topological structure and detailed features of the model. Compared to the QEM algorithm and the other two comparison algorithms selected in this paper, the simplified model resulting from this algorithm exhibit a reduction in Hausdorff distance, mean error, and mean square error to varying degrees. Moreover, the advantages of this algorithm become more pronounced as the simplification rate increases. The research findings can be applied to the simplification of 3D building models.

Review of Three-Dimensional Model Simplification Algorithms Based on Quadric Error Metrics and Bibliometric Analysis by Knowledge Map

With the rapid advancement of computer graphics and three-dimensional modeling technology, the processing and optimization of three-dimensional (3D) models have become contentious research topics. In the context of mobile devices or web applications, situations may arise where it becomes necessary to load a 3D model with a substantial memory footprint in real-time or dynamically adjust the level of detail of a model based on the scene’s proximity. In such cases, it is imperative to optimize the original model to ensure smoothness and responsiveness. Due to the simplicity of their algorithm, quadric error metrics (QEMs) can deliver excellent results in simplifying 3D models while maintaining high efficiency. Therefore, QEM is widely employed in engineering applications within the realm of computer graphics development. Moreover, in the pursuit of enhanced quality and efficiency, numerous scholars have improved it based on QEM algorithms. This study aims to provide a systematic review and summary of the principles and applications of current research on QEM algorithms. First, we conducted a bibliometric analysis of 128 studies in related fields spanning from 1998 to 2022 using CiteSpace. This allowed us to sort QEM algorithms and gain insights into their development status and emerging trends. Second, we delve into the fundamental principles and optimizations of the QEM algorithms to provide a deeper understanding of their implementation process. Following that, we explore the advantages and limitations of the QEM algorithms in practical applications and analyze their potential in various domains, including virtual reality and game development. Finally, this study outlines future research directions, which encompass the development of more efficient error metric calculation methods, the exploration of adaptive simplification strategies, and the investigation of potential synergies with deep learning technologies. Current research primarily centers on enhancing QEM algorithms by incorporating additional geometric constraints to better differentiate between flat and irregular areas. This enables a more accurate determination of the areas that should be prioritized for folding. Nevertheless, it is important to note that these improvements may come at the cost of reduced computational efficiency. Therefore, future research directions could involve exploring parallel computing techniques and utilizing GPUs to enhance computational efficiency.

A Model Simplification Algorithm for 3D Reconstruction

Mesh simplification is an effective way to solve the contradiction between 3D models and limited transmission bandwidth and smooth model rendering. The existing mesh simplification algorithms usually have problems of texture distortion, deformation of different degrees, and no texture simplification. In this paper, a model simplification algorithm suitable for 3D reconstruction is proposed by taking full advantage of the recovered 3D scene structure and calibrated images. First, the reference 3D model scene is constructed on the basis of the original mesh; second, the images are collected on the basis of the reference 3D model scene; then, the mesh and texture are simplified by using the reference image set combined with the QEM algorithm. Lastly, the 3D model data of a town in Tengzhou are used for experimental verification. The results show that the algorithm proposed in this paper basically has no texture distortion and deformation problems in texture simplification and can effectively reduce the amount of texture data, with good feasibility.

An improved texture-related vertex clustering algorithm for model simplification

As an important data source in 3D GIS, 3D landmark models are built to simulate the real-world scenario. However, due to the enormous volume and complexity of 3D models, the data transmission under limited bandwidth and the real-time rendering have always been an open problem. In order to improve the visualization and the efficiency, this paper proposes a novel model simplification algorithm in consideration of texture after the analysis of the existing model simplification approaches. Differing from the previous research, our approach defines a new error metric related to the model texture, which extends the vertex clustering scheme in 3D geometry space and 2D texture space independently. Since the uneven distribution of vertices is taken into account, the clustering unit is divided adaptively in consideration of both geometry and texture information. In view of reducing the memory overhead and improving the algorithm efficiency, we don’t create new vertices by iterative calculations, but use the inherent vertices in the initial meshes as the characteristic vertices. To demonstrate the feasibility and effectiveness of our strategy, a series of simplification experiments have been carried out on the platform of DirectX 3D, a widely used 3D application programming interface. The results show that the simplified models in consideration of texture preserve more texture details than those traditional ones. It apparently makes a good balance between the reduction rate and visual effects.

Texture Model Simplification Algorithm Based on Feature Preserving

In order to keep the geometric shape and texture of the model in the process of model simplification, this paper proposes a simplification algorithm based on feature preserved for model with texture. By finding the feature points and odd points of the model controlling the point selection to collapse edge for simplifying model. Angle between normal vectors of the edges two vertices and the area of the triangles adjacent to the edge are introduced in the QEM algorithm as the error factor to redefine the cost of edge collapse, finally better keep the feature of model. This paper uses Mipmap technology to generate multi-resolution texture maps so that improves the efficiency when rendering model in real time.

GPU based generation of state transition models using simulations for unmanned surface vehicle trajectory planning

This paper describes GPU based algorithms to compute state transition models for unmanned surface vehicles (USVs) using 6 degree of freedom (DOF) dynamics simulations of vehicle–wave interaction. A state transition model is a key component of the Markov Decision Process (MDP), which is a natural framework to formulate the problem of trajectory planning under motion uncertainty. The USV trajectory planning problem is characterized by the presence of large and somewhat stochastic forces due to ocean waves, which can cause significant deviations in their motion. Feedback controllers are often employed to reject disturbances and get back on the desired trajectory. However, the motion uncertainty can be significant and must be considered in the trajectory planning to avoid collisions with the surrounding obstacles. In case of USV missions, state transition probabilities need to be generated on-board, to compute trajectory plans that can handle dynamically changing USV parameters and environment (e.g., changing boat inertia tensor due to fuel consumption, variations in damping due to changes in water density, variations in sea-state, etc.). The 6 DOF dynamics simulations reported in this paper are based on potential flow theory. We also present a model simplification algorithm based on temporal coherence and its GPU implementation to accelerate simulation computation performance. Using the techniques discussed in this paper we were able to compute state transition probabilities in less than 10 min. Computed transition probabilities are subsequently used in a stochastic dynamic programming based approach to solve the MDP to obtain trajectory plan. Using this approach, we are able to generate dynamically feasible trajectories for USVs that exhibit safe behaviors in high sea-states in the vicinity of static obstacles.

3D Models Simplification Algorithm for Mobile Devices

As we know, the mobile device screen is small. The lower accuracy of the model is relatively weak and the capacity to handle high detailed model is very limited. What’s more, the existing three-dimensional simplification algorithms are for the personal computer and they are not suitable for the mobile terminals. Thus, we propose a novel 3D model simplification algorithm based on feature points. We will find the model surface curvature of each vertex, based on the model feature points. For these points, we present a new method to obtain it. Experimental results show that the algorithm can accurately reflect the model changes of the local surface geometry, and effectively keep the details of the model characteristics.

An element-oriented model simplification algorithm based on dynamic similarity

This paper presents an element-oriented model simplification algorithm (EO-MSA) in multi-physical domains. It aims to generate a simplified model to release computational loading while maintaining model fidelity. The dynamics of the multi-physical system can be constructed based on a unified bond graph approach. This EO-MSA approach eliminates those bond graph elements which influence the system behaviour insignificantly in the mathematical model. This study proposes two newly-defined indices, dynamic similarity ( DS), and model similarity index ( MSI), to evaluate the similarity of candidates which are order reduced. Ten error-dynamics modules are mathematically constructed and structurally classified for both the DS and the MSI. The reduced model with minimum MSI can be determined using this approach. Quarter-car simulation results demonstrate that this EO-MSA approach is capable of reducing system complexity while maintaining fidelity with satisfactory tolerance.

Real-Time Dynamics Simulation of Unmanned Sea Surface Vehicle for Virtual Environments

Abstract The role of virtual environments (VEs) is crucial in efficient design and operation of unmanned vehicles. VEs are extensively used in operator training for tele-operation, planning using programming by demonstration, and hardware and software designs. VE for unmanned sea surface vehicles (USSV) requires a 6 degree of freedom dynamics simulation in the time domain. In order to be interactive, the VE requires real-time performance of the underlying dynamics simulator. In general, the dynamics simulation of USSVs involves the following four main operations: (1) computation of dynamic pressure head due to fluid flow around the hull under the ocean wave, (2) computation of wet surface, (3) computing the surface integral of the dynamic pressure head over the wet surface, and (4) solving the rigid body dynamics equation. The first three operations depend upon the boat geometry complexity and need to be performed at each time step, making the simulation run very slow. In this paper, we address the problem of physics preserving model simplification for real-time potential flow based simulator for a USSV in the time domain, with an arbitrary hull geometry. This paper reports model simplification algorithms based on clustering, temporal coherence, and hardware acceleration using parallel computing on multiple cores to obtain real time simulation performance for the developed VE.

Feature-Based Simplification of Process Plant Models over Network

Visualization of 3D process plant models is an essential feature to support design review in distributed design environment. The preprocessing time, frame rate and visual fidelity play the same import role in improving the effectiveness and efficiency of the entire design review process. General model simplification algorithms, such as levels of detail (LODs) and hierarchical levels of detail (HLODs), always need unbearable time for preprocessing large-scale models and may distort design feature and make them unrecognizable to the reviewer. To efficiently transmit models, various compression technologies can be applied to shrink the data size. However, transmitting large-scale models over network is still a bottleneck of rendering performance. In this paper, we presented a new, faster feature-based model simplification algorithm to simplify process plant models over network. We first get the model's geometric parameters and topology information from the server before visualization. Then we compute LODs and HLODs according to the model�s geometric parameters and composing feature on the client. No triangles are transmitted during visualization. We demonstrate its performance on complex process plant models composed of tens of millions of triangles. Results show that our approach is able to shorten the preprocessing time greatly. And it can achieve considerable speedups in frame rate with little loss in image quality.

Complex model simplification algorithm with improved error evaluation

Given the framework of incremental mesh simplification based on edge colapse, the paper proposes a mesh simplification algorithm using an improved approach for measuring simplification error. The algorithm uses edge collapse to simplify the triangle mesh and maintains surface error approxinations using c-error for the faces which have changed after edge collapse and d-error for the faces which become degenerated after edge collapse. Also, we report some results using a variety of computer graphics models, which can show that the algorithm can achieve the desired simplification effect.