A linked feature space approach to exploring LIDAR data.
Harrison, Lane T.
- A typical approach to exploring Light Detection and Ranging (LIDAR) datasets is to extract features using pre-defined segmentation algorithms. However, this approach only provides a limited set of features that users can investigate. To expand and represent the rich information inside the LIDAR data, we introduce a linked feature space concept that allows users to make regular, conjunctive, and ... read moredisjunctive discoveries in non-uniform LIDAR data by interacting with multidimensional transfer functions. We achieve this by providing interactions for creating multiple scatter-plots of varying axes, establishing chains of plots based on selection domains, linking plots using logical operators, and viewing selected brushing results in both a 3D view and selected scatter-plots. Our highly interactive approach to visualizing LIDAR feature spaces facilitates the users' ability to explore, identify, and understand data features in a novel way. Our approach for exploring LIDAR data can directly lead to better understanding of historical LIDAR datasets, and increase the turnaround time and quality of results from time-critical LIDAR collections after urban disasters or on the battlefield. Copyright 2010 Society of Photo-Optical Instrumentation Engineers (SPIE) One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.read less
- Lane Harrison, Thomas Butkiewicz, Xiaoyu Wang, William Ribarsky, Remco Chang, "A linked feature space approach to exploring lidar data", Proc. SPIE 7709, Cyber Security, Situation Management, and Impact Assessment II; and Visual Analytics for Homeland Defense and Security II, 77090X (28 April 2010); doi: 10.1117/12.850579; http://dx.doi.org/10.1117/12.850579.