Interactive 3D Segmentation of Rock-Art by Enhanced Depth Maps and Gradient Preserving Regularization
| Autor: | Christian Breiteneder, Georg Poier, Horst Bischof, Christian Reinbacher, Markus Seidl, Matthias Zeppelzauer, Samuel Schulter |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
060102 archaeology
Segmentation-based object categorization business.industry Computer science 3D reconstruction Point cloud Scale-space segmentation 06 humanities and the arts 02 engineering and technology Conservation Computer Graphics and Computer-Aided Design Computer Science Applications Computer graphics (images) 0202 electrical engineering electronic engineering information engineering Petroglyph 020201 artificial intelligence & image processing 0601 history and archaeology Computer vision Segmentation Artificial intelligence Rock art business Digitization Information Systems |
| Zdroj: | TU Graz |
| ISSN: | 1556-4711 1556-4673 |
| DOI: | 10.1145/2950062 |
| Popis: | Petroglyphs (rock engravings) have been pecked and engraved by humans into natural rock surfaces thousands of years ago and are among the oldest artifacts that document early human life and culture. Some of these rock engravings have survived until the present and serve today as a unique document of ancient human life. Since petroglyphs are pecked into the surface of natural rocks, they are threatened by environmental factors such as weather and erosion. To document and preserve these valuable artifacts of human history, the 3D digitization of rock surfaces has become a suitable approach due to the development of powerful 3D reconstruction techniques in recent years. The results of 3D reconstruction are huge 3D point clouds which represent the local surface geometry in high resolution. In this article, we present an automatic 3D segmentation approach that is able to extract rock engravings from reconstructed 3D surfaces. To solve this computationally complex problem, we transfer the task of segmentation to the image-space in order to efficiently perform segmentation. Adaptive learning is applied to realize interactive segmentation and a gradient preserving energy minimization assures smooth boundaries for the segmented figures. Our experiments demonstrate the efficiency and the strong segmentation capabilities of the approach. The precise segmentation of petroglyphs from 3D surfaces provides the foundation for compiling large petroglyph databases which can then be indexed and searched automatically. |
| Databáze: | OpenAIRE |
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