Name
Abstract | ||
|---|---|---|
The Video Event Awareness System (VEAS) analyzes surveillance video from thousands of video cameras and automatically detects complex events in near real-time-at pace with their input video streams. For events of interest to security personnel, VEAS generates and routes alerts and related video evidence to subscribing security personnel that facilitate decision making and timely response. In this paper we introduce VEAS's novel publish/subscribe run-time system architecture and describe VEAS's event detection approach. Event processing in VEAS is driven by user-authored awareness specifications that define patterns of inter-connected spatio-temporal event stream operators that consume and produce facility-specific events described in VEAS's surveillance ontology. We describe how VEAS integrates and orchestrates continuous and tasked video analysis algorithms (e.g., for entity tracking and identification), how it fuses events from multiple sources and algorithms in an installation-specific entity model, how it can proactively seek additional information by tasking video analysis algorithms and security personnel to provide it, and how it deals with late arriving information due to out-of-band video analysis tasks and overhead. We use examples from the physical security domain, and discuss related and future work. |
Year | Venue | Keywords |
|---|---|---|
2006 | SIGMAP 2006: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING AND MULTIMEDIA APPLICATIONS | video surveillance,event processing,situation awareness |
Field | DocType | Citations |
Physical security,Computer security,Computer science,Security information and event management,Multimedia | Conference | 3 |
PageRank | References | Authors |
0.71 | 1 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dimitrios Georgakopoulos | 1 | 2554 | 580.54 |
| Donald Baker | 2 | 380 | 77.88 |