Schematic Querying of Large Tracking Databases
Author(s)Dalley, Gerald; Izo, Tomas
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In dealing with long-term tracking databases withwide-area coverage, an important problem is in formulating anintuitive and fast query system for analysis. In such a querysystem, a user who is not a computer vision research should beable to readily specify a novel query to the system and obtainthe desired results. Furthermore, these queries should be able tonot only search out individual actors (e.g. "find all white cars")but also find interactions amongst multiple actors (e.g. "find alldrag racing activities in the city"). Informally, we have foundthat people often use sketches when describing activities andinteractions. In this paper, we demonstrate a preliminary systemthat automatically interprets schematic drawings of activities.The system transforms the schematics into executable code thatsearches a tracking database. Through our query optimization,these queries tend to take orders of magnitude less time to executethan equivalent queries running on a partially-optimized SQLdatabase.
Massachusetts Institute of Technology Computer Science and Artificial Intelligence Laboratory