Sketch-Based Spatial Queries for Retrieving Human Locomotion Patterns From Continuously Archived GPS Data

We propose a system for retrieving human locomotion patterns from tracking data captured within a large geographical area, over a long period of time. A GPS receiver continuously captures data regarding the location of the person carrying it. A constrained agglomerative hierarchical clustering algorithm segments these data according to the person's navigational behavior. Sketches made on a map displayed on a computer screen are used for specifying queries regarding locomotion patterns. Two basic sketch primitives, selected based on a user study, are combined to form five different types of queries. We implement algorithms to analyze a sketch made by a user, identify the query, and retrieve results from the collection of data. A graphical user interface combines the user interaction strategy and algorithms, and allows hierarchical querying and visualization of intermediate results. We evaluate the system using a collection of data captured during nine months. The constrained hierarchical clustering algorithm is able to segment GPS data at an overall accuracy of 94% despite the presence of location-dependent noise. A user study was conducted to evaluate the proposed user interaction strategy and the usability of the overall system. The results of this study demonstrate that the proposed user interaction strategy facilitates fast querying, and efficient and accurate retrieval, in an intuitive manner.