MRI: Acquisition of Light Detection and Ranging (LIDAR) Scanner for Computer Vision Research and Interdisciplinary Education

University Of North Carolina At Wilmington, Wilmington NC

Investigators

Abstract

This project, acquiring a Leica ScanStation P30, aims to develop methods for aligning two dimensional (2D) and three dimensional (3D) data and to assemble educational tools using the produced 3D visualizations. The LIDAR (LIght Detection And Ranging) scanner will be used by professors and students studying and performing research in the fields of computer science, film, and art at the institution. The group builds on the researcher's existing work that creates navigable 3D environments from sets of 2D pictures and videos that are registered with 3D LIDAR scans. With the instrumentation this project would enable the following intertwined goals. (i) Build an interdisciplinary research group to further study how to describe and register multi-modality data, or data obtained with different cameras and sensors. (ii) Use the developed methods to build educational 3D applications with collaborators in film and history. (iii) Develop new, cross-disciplinary courses that use the proposed scanner to provide access for many students to the state-of-the-art technology. The developed courses would help the investigator train and recruit students for her research lab that can work on interdisciplinary projects. Although at present collecting and storing both 2D images and 3D LIDAR scans might be easier and more economical, fusing such multi-modality data remains challenging. Confusion is often created in automatic matching methods by the repetition and ambiguity that often occur in man-made scenes as well as the variety of properties on different renderings of the same subject. Image sets collected over a period of time during which lighting conditions and scene content may have changed, different artistic rendering, as well as varying sensor types (Camera, LIDAR, etc.), can all contribute to visual variations in data sets. However, by incorporating contextual information to visualize the regional properties that intuitively exist in each imagery source, the proponent has successfully addressed many of the obstacles. Her research group will also study how human perception can be used for registering 3D LIDAR data with other types of visual information.