Improvements in three-dimensional (3D) scanning have enabled quick and accurate scanning of 3D objects, including cultural heritage objects, as 3D point cloud data. However, conventional edge-highlighting visualization techniques, used for understanding complex 3D structures, result in excessive line clutter, reducing clarity. Addressing these issues, a multinational team of researchers have developed a novel edge detection technique, involving independent rendering of soft and sharp edges in 3D structures, resulting in improved clarity and depth perception.
From an article in Science Daily by Ritsumeikan Univ.
Recent advances in three-dimensional (3D) scanning, particularly in photogrammetry and laser scanning, have made it possible to quickly and accurately scan complex 3D objects in the real world. These techniques generate detailed models by collecting large-scale point cloud data, representing the object’s surface geometry through millions of individual points. This technology has applications in different fields, such as the 3D scanning of cultural heritage objects. By preserving these objects in digital formats, researchers can analyze their structures in greater depth. However, the complexity of data is often significant, especially when the scanned object has internal 3D structures, like rough edges.
Edge-highlighting visualization is a technique used to improve the clarity of complex 3D structures by emphasizing the object’s edges, making its shape and structure more distinguishable. However, existing methods struggle when applied to highly complex objects. These methods draw too many lines, which decreases clarity by impairing resolution and depth perception.
To address these challenges, a multinational team of researchers, led by Professor Satoshi Tanaka, along with colleagues Ms. Yuri Yamada, Dr. Satoshi Takatori, and Prof. Liang Li from the College of Information Science and Engineering at Ritsumeikan University, have developed an innovative method. Elaborating on their study, Prof. Tanaka explains, “Conventional methods for extracting and visualizing 3D edges mainly concentrate on sharp edges. However, many real-world objects contain numerous soft edges in addition to sharp edges, which are inadequately represented. Our method introduces two key innovations: dual 3D edge extraction, which separately extracts both soft and sharp edges, and opacity-color gradation, which enhances the clarity of soft edges through variations in color and opacity.” These findings were published in Remote Sensing on October 09, 2024.
For the complete article on edge detection CLICK HERE.
Note – If you have a lidar related news story that you would like us to promote, please forward to editor@lidarnews.com and if you would like to join the Younger Geospatial Professional movement click here
