Pfinder: Real-Time Tracking of the Human Body
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning Patterns of Activity Using Real-Time Tracking
IEEE Transactions on Pattern Analysis and Machine Intelligence
W4: Real-Time Surveillance of People and Their Activities
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Real-Time System for Monitoring of Cyclists and Pedestrians
VS '99 Proceedings of the Second IEEE Workshop on Visual Surveillance
Illumination Normalization with Time-Dependent Intrinsic Images for Video Surveillance
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image segmentation in video sequences: a probabilistic approach
UAI'97 Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence
Detection and classification of vehicles
IEEE Transactions on Intelligent Transportation Systems
Detection of moving cast shadows for object segmentation
IEEE Transactions on Multimedia
Detecting moving objects, ghosts, and shadows in video streams
IEEE Transactions on Pattern Analysis and Machine Intelligence
An algorithm for recovering camouflage errors on moving people
SSPR&SPR'10 Proceedings of the 2010 joint IAPR international conference on Structural, syntactic, and statistical pattern recognition
An experimental evaluation of foreground detection algorithms in real scenes
EURASIP Journal on Advances in Signal Processing - Special issue on video analysis for human behavior understanding
| Hi-index | 0.00 |
In a video surveillance system, moving object detection is the most challenging problem especially if the system is applied to complex environments with variable lighting, dynamic and articulate scenes, etc. Furthermore, a video surveillance system is a real-time application, so discouraging the use of good, but computationally expensive, solutions. This paper presents a set of improvements of a basic background subtraction algorithm that are suitable for video surveillance applications. Besides we present a new performance evaluation scheme never used in the context of moving object detection algorithms.