Show simple item record

dc.contributor.advisorEric Grimson
dc.contributor.authorDalley, Gerald
dc.contributor.authorIzo, Tomas
dc.contributor.otherVision
dc.date.accessioned2006-06-12T18:36:58Z
dc.date.available2006-06-12T18:36:58Z
dc.date.issued2006-06-12
dc.identifier.otherMIT-CSAIL-TR-2006-043
dc.identifier.urihttp://hdl.handle.net/1721.1/32999
dc.description.abstractIn 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.
dc.format.extent7 p.
dc.format.extent391836 bytes
dc.format.extent7529339 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypeapplication/postscript
dc.language.isoen_US
dc.relation.ispartofseriesMassachusetts Institute of Technology Computer Science and Artificial Intelligence Laboratory
dc.titleSchematic Querying of Large Tracking Databases


Files in this item

Thumbnail
Thumbnail

This item appears in the following Collection(s)

Show simple item record