In this paper, we present a new technique to remove specular effects from the photo-grammetric results in a automatic photogrammetric workflow for Architectural Heritage (AH) 3D model construction. Our solution provides a new reconstruction pipeline completely integrated in the automatic photogrammetric pipeline re-using existing data to arrange new results. The process of acquisition of the images to get the finished 3D model is therefore unique and the process for acquiring and visualizing the correct perceived color is fully integrated with the process of shape capture. Overall, the method does not require specific technical knowledge, being therefore relatively easy to use, and it can be used over many different urban settings and contexts. The proposed methodology is a high-level image-processing algorithm. As such, it uses several lower-level methods for its building blocks. We consider these methods as black boxes, and we explain below their input, output and purpose. We demonstrated the efficiency of our method using case study of our work in many cases of the ca 43 km of historical porticoes system in Bologna, Italy, a superset of the family of AH objects that it belongs to.
Highlight and specular reflection removal in photogrammetric techniques applied to architectural heritage 3D modeling
APOLLONIO, FABRIZIO IVAN;BALLABENI, ANDREA;GAIANI, MARCO
2017
Abstract
In this paper, we present a new technique to remove specular effects from the photo-grammetric results in a automatic photogrammetric workflow for Architectural Heritage (AH) 3D model construction. Our solution provides a new reconstruction pipeline completely integrated in the automatic photogrammetric pipeline re-using existing data to arrange new results. The process of acquisition of the images to get the finished 3D model is therefore unique and the process for acquiring and visualizing the correct perceived color is fully integrated with the process of shape capture. Overall, the method does not require specific technical knowledge, being therefore relatively easy to use, and it can be used over many different urban settings and contexts. The proposed methodology is a high-level image-processing algorithm. As such, it uses several lower-level methods for its building blocks. We consider these methods as black boxes, and we explain below their input, output and purpose. We demonstrated the efficiency of our method using case study of our work in many cases of the ca 43 km of historical porticoes system in Bologna, Italy, a superset of the family of AH objects that it belongs to.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
