Solving the multiple instance problem with axis-parallel rectangles
Artificial Intelligence
Comparing Images Using the Hausdorff Distance
IEEE Transactions on Pattern Analysis and Machine Intelligence
Implicit and Explicit Camera Calibration: Theory and Experiments
IEEE Transactions on Pattern Analysis and Machine Intelligence
BilVideo: A Video Database Management System
IEEE MultiMedia
ICML '02 Proceedings of the Nineteenth International Conference on Machine Learning
Multiple-Instance Learning for Natural Scene Classification
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
ICMCS '97 Proceedings of the 1997 International Conference on Multimedia Computing and Systems
A Survey of Camera Self-Calibration
AVSS '03 Proceedings of the IEEE Conference on Advanced Video and Signal Based Surveillance
Enabling Video Privacy through Computer Vision
IEEE Security and Privacy
Supervised versus multiple instance learning: an empirical comparison
ICML '05 Proceedings of the 22nd international conference on Machine learning
ISM '05 Proceedings of the Seventh IEEE International Symposium on Multimedia
ACM Computing Surveys (CSUR)
Incremental assignment problem
Information Sciences: an International Journal
Multimedia Tools and Applications
Multi-camera people tracking by collaborative particle filters and principal axis-based integration
ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part I
Detection of user-defined, semantically high-level, composite events, and retrieval of event queries
Multimedia Tools and Applications
Scrambling for Privacy Protection in Video Surveillance Systems
IEEE Transactions on Circuits and Systems for Video Technology
Real-Time Query Processing on Live Videos in Networks of Distributed Cameras
International Journal of Interdisciplinary Telecommunications and Networking
| Hi-index | 0.00 |
Omnipresent camera networks have been a popular research topic in recent years. They are applicable to a range of monitoring tasks, from bridges to gas stations to the inside of industrial chemical tanks. Though a large body of existing work focuses on image and video processing techniques, very few address the usability of such systems or the implications of real-time video dissemination. In this article, we present our work on extending the LVDBMS prototype with a multifaceted object model to characterize objects in live video streams. This forms the basis for a cross-camera tracking framework which permits objects to be tracked from one video stream to another. With this infrastructure, real-time queries may be posed to monitor complex events that occur in multiple video streams simultaneously. This live video database environment provides a general-purpose platform for distributed live video computing with the goal of enabling rapid application development for camera networks.