Abstract
This evaluation for person and vehicle tracking in surveillance presented some new challenges. The dataset was large and very high-quality, but with difficult scene properties involving illumination changes, unusual lighting conditions, and complicated occlusion of objects. Since this is a well-researched scenario [1], our submission was based primarily on our existing projects for automated object detection and tracking in surveillance. We also added several new features that are practical improvements for handling the difficulties of this dataset.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 174-178 |
| Number of pages | 5 |
| Journal | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
| Volume | 4625 LNCS |
| DOIs | |
| State | Published - Jul 28 2008 |
| Externally published | Yes |
| Event | 2nd Annual Classifcation of Events Activities and Relationships, CLEAR 2007 and Rich Transcription, RT 2007 - Baltimore, MD, United States Duration: May 8 2007 → May 11 2007 |
ASJC Scopus subject areas
- Theoretical Computer Science
- Computer Science(all)