Intelligent 3D world building from mobile terrestrial LiDAR point clouds

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Mobile laser scanning (MLS) provides fast, efficient and cost-effective data collection. As studies carried out by various early adopters of this technology have highlighted, using mobile laser scanning allows cutting down field times by 80-90% but increases back office processing by 200-300%. The processing challenge comes from the difficulty of distinguishing different feature types from the huge amount of laser points. Even if some efficient numerical algorithms can be applied to speed up the 3D point cloud processing, they often rely on significant interaction of the user. The significant "value add" in the MLS workflow comes in transforming 3D georeferenced point clouds into intelligent 3D models of our urban infrastructure and environment. Not only is this type of semantic description significantly more compact than the raw data, but it supports high-level tasks like analysis of space usage or planning for renovations. This is the real challenge currently facing this field.The long-term objective of the proposed research program aims at designing new methodology and processing solutions to efficiently build intelligent 3D worldsfrom mobile terrestrial LiDAR point clouds. This objective depends upon speeding up the process of detecting and extracting significant structures from the huge amount of registered data, providing models including geometric and functional knowledge, and fusing MLS point clouds with complementary data sets, yielding multi-scale and multi-mode representations. The cornerstone of the proposed research work is the concept of interest point and related 3d descriptors adapted to MLS point clouds. There has been little research on such a topic in the past, compared to computer vision where this is a well researched area. The concept of MLS interest point could have strong impact on the capability and facilityto create multi-scale 3D models and to attach semantics to these models. This would help meeting the current tremendous need for geo-information which has to be more up to date, more 3D, more accessible over the Internet.