Comparison of ZEB1 and Leica C10 indoor laser scanning point clouds

We present a comparison of point cloud generation and quality of data acquired by Zebedee (Zeb1) and Leica C10 devices which are used in the same building interior. Both sensor devices come with different practical and technical advantages. As it could be expected, these advantages come with some drawbacks. Therefore, depending on the...

Quality assessment and comparison of smartphone, airborne and leica c10 laser scanner based point clouds

3D urban models are valuable for urban map generation, environment monitoring, safety planning and educational purposes. For 3D measurement of urban structures, generally airborne laser scanning sensors or multi-view satellite images are used as a data source. However, close-range sensors (such as terrestrial laser scanners) and low cost cameras...

Active Shapes for Automatic 3D Modeling of Buildings

Recent technological developments help us to acquire high quality 3D measurements of our urban environment. However, these measurements, which come as point clouds or Digital Surface Models (DSM), do not directly give 3D geometrical models of buildings. In addition to that, they are not suitable for fast 3D rendering. Therefore, detection and 3D...

A semi-automatic procedure for texturing of laser scanning point clouds with google streetview images

We introduce a method to texture 3D urban models with photographs that even works for Google Streetview images and can be done with currently available free software. This allows realistic texturing, even when it is not possible or cost-effective to (re)visit a scanned site to take textured scans or photographs. Mapping a photograph onto a 3D...

Automatic classification of trees from laser scanning point clouds

Development of laser scanning technologies has promoted tree monitoring studies to a new level, as the laser scanning point clouds enable accurate 3D measurements in a fast and environmental friendly manner. In this paper, we introduce a probability matrix computation based algorithm for automatically classifying laser scanning point clouds into...

Accuracy assessment of building point clouds automatically generated from iphone images

Low-cost sensor generated 3D models can be useful for quick 3D urban model updating, yet the quality of the models is questionable. In this article, we evaluate the reliability of an automatic point cloud generation method using multi-view iPhone images or an iPhone video file as an input. We register such automatically generated point cloud...

Automatic registration of iPhone images to laser point clouds of urban structures using shape features

Fusion of 3D airborne laser (LIDAR) data and terrestrial optical imagery can be applied in 3D urban modeling and model up-dating. The most challenging aspect of the fusion procedure is registering the terrestrial optical images on the LIDAR point clouds. In this article, we propose an approach for registering these two different data from...