Geometric hashing for camera based localization
Wei Tan · 2012
The most popular localization system now, Global Positioning System (GPS), is well known for its limitation in high rise urban areas due to difficulty in establishing line of sight to multiple GPS satellites.A vision or camera based localization system is an interesting alternative to consider for localization.A camera based localization system has been established previously [1], assuming that the only available prior information is a two-dimensional (2D) plan view of a city region.Given a query image taken in the same city region, the basic approach of localization is to establish correspondence between the query image and the 2D map, based on a new feature called Vertical Corner Line Hypothesis (VCLH), hypothesis of a vertical building corner in an image.A VCLH is characterized by position of the vertical line or building corner in the image, and orientations of the neighbouring plane normal.The set of VCLHs extracted from the input image is called VCLH signature.Matching is performed by identifying the camera position on the 2D map with the closest VCLH signature to the input image one using Random Sample Consensus (RANSAC) [2].However, the search for best camera location is computationally expensive.Hence, this project aims to develop a speedup framework to solve the problem.Geometric Hashing [3], hashing based on geometric information such as keypoints invariant to translation and rotation, is employed in this project.