Real-time object classification and novelty detection for collaborative video surveillance

Proceedings of the International Joint Conference on Neural Networks

Volumn 3, Issue , 2002, Pages 2620-2625

  Diehl, Christopher P ^a   Hampshire II, John B ^a  

^a JOHNS HOPKINS UNIVERSITY APPLIED PHYSICS LABORATORY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER SUPPORTED COOPERATIVE WORK; EDGE DETECTION; LEARNING SYSTEMS; OBJECT RECOGNITION; OPTIMAL SYSTEMS; REAL TIME SYSTEMS; USER INTERFACES; VIDEO SIGNAL PROCESSING;

COLLABORATIVE VIDEO SURVEILLANCE; COMMERCIAL OFF-THE-SHELF HARDWARE; REAL TIME OBJECT CLASSIFICATION; REAL TIME OBJECT DETECTION;

PATTERN RECOGNITION SYSTEMS;

EID: 0036080023     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (18)

1. The PASSWORDS project
2. Advanced visual surveillance using Bayesian networks
3. On optimum recognition error and reject trade-off
4. Toward efficient collaborative classification for distributed video surveillance
5. Pattern classification and scene analysis
6. Autonomous video surveillance
7. Object recognition and tracking for remote video surveillance
8. Using adaptive tracking to classify and monitor activities in a site
9. A differential theory of learning for efficient statistical pattern recognition
10. Advances in cooperative multi-sensor video surveillance
11. Trainable pedestrian detection
12. Novelty, confidence and errors in connectionist systems
13. Improving the generalization of linear support vector machines: An application to 3D object recognition with cluttered background
14. View-based 3D object recognition with support vector machines
15. CyberScout: Distributed agents for autonomous reconnaissance and surveillance
16. A statistical model for 3D object detection applied to faces and cars
17. SV estimation of a distribution's support
18. Robust real-time object detection