Meshlab polygon reduction
In this paper we present an improved quadric error metric for simplifying meshes with attributes. This quadric approach was recently generalized to handle meshes with appearance attributes. Previous work has shown that a quadric error metric allows fast and accurate geometric simplification of meshes. After the comparative evaluation of different low-poly algorithms and the generation of a test model, a PostgreSQL DBMS and a front-end PHP interface were developed to allow users to analyze and query the model.Ĭomplex triangle meshes arise naturally in many areas of computer graphics and visualization. The main idea is to create simple geometries (through low-poly algorithms) to significantly reduce the number of polygons in the reality-based environment and publish the model on the web. In this paper, we analyze recent low-poly methods aimed at reducing the size and complexity of 3D models applied to the case study of an historical building of Bari (Italy). Furthermore, it is also more difficult for citizens to access 3D models aimed at tourism and education. The large size and complex nature of data makes it difficult for heritage experts to manage them for run more complex spatial analyses. Nowadays several computer applications and IT instruments are available for the management of cultural, archaeological and environmental heritages. In recent years, the rising popularity of 3D models in the field of Cultural Heritage has brought additional geo-spatial formats for its documentation, making necessary to test new approaches in managing, publishing and studying heterogeneous data in an integrated way. As a future study, MeshLab Clustering Decimation has potential in artificial intelligence studies in designing new objects. On the other hand, MeshLab Clustering Decimation is more efficient at creating a new form without losing fidelity, but it cannot produce models in every level of detail. Blender Decimate-Collapse is more efficient at preserving the geometry to low levels of detail, so it is the best abstraction method of fidelity.
![meshlab polygon reduction meshlab polygon reduction](https://image.slideserve.com/1424563/slide9-l.jpg)
Therefore, it is efficient for saving time. As a result, 3ds Max ProOptimizer comes forward as the most efficient tool to reduce the file size. Accordingly, algorithms are evaluated within and compared with each other.
![meshlab polygon reduction meshlab polygon reduction](https://www.mdpi.com/ijms/ijms-19-01383/article_deploy/html/images/ijms-19-01383-g014-550.jpg)
The comparison criteria are (i) geometric change/level of fidelity, (ii) number of polygons, and (iii) file size.
![meshlab polygon reduction meshlab polygon reduction](https://www.frontiersin.org/files/Articles/441914/fmech-05-00033-HTML/image_m/fmech-05-00033-g002.jpg)
Low poly sphere models in different levels of detail are produced from each algorithm. In this paper, polygon reduction algorithms named (i) Decimate-Collapse in Blender 2.80, (ii) ProOptimizer in 3dsMax 2019, and (iii) "Clustering Decimation" in MeshLab 2019 are compared through sphere geometry to understand the potential of low poly modeling. There are various simplification methods via different software. Besides decreasing the file size, novel designs may be developed by simplifying the 3D objects by low poly modeling. Low Poly Modeling, as one of the most common abstraction methods, initially emerged to maximize the efficiency of the digital modeling process.