Precise 3D Reconstruction of Cultural Objects Using Combined Multi-component Image Matching and Active Contours Segmentation.

Cultural and creative industries constitute a large range of economic activities. Towards this expansion we need to state the inclusion of ICT technologies, as such of 3D reconstruction methods. However, precise 3D reconstruction under a computationally affordable manner is a research challenge. One way to precisely reconstruct a cultural object is through the use of photogrammetry with the main goal of finding the correspondences between two or more images to reconstruct 3D surfaces. A cultural object is often surrounded by visual background data that should be excluded to improve 3D reconstruction accuracy. Background conditions dynamically change, especially if the object is captured under outdoor conditions, where many occlusions occur and the shadows effects are not negligible. In this paper, we propose a combine image segmentation and matching method to yield an affordable 3D reconstruction of cultural objects. Image segmentation is performed on the use of active contours while image matching through novel multi-cost criteria optimization functions. Experimental results on real-life ancient column capitals indicate the efficiency of the proposed scheme both in terms of performance efficiency and cost.