Oriented projective geometry
Monitoring Activities from Multiple Video Streams: Establishing a Common Coordinate Frame
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
Multi View Image Surveillance and Tracking
MOTION '02 Proceedings of the Workshop on Motion and Video Computing
Objects Detection with Multiple Cameras
MOTION '02 Proceedings of the Workshop on Motion and Video Computing
Continuous Multi-Views Tracking using Tensor Voting
MOTION '02 Proceedings of the Workshop on Motion and Video Computing
Adaptive Change Detection for Real-Time Surveillance Applications
VS '00 Proceedings of the Third IEEE International Workshop on Visual Surveillance (VS'2000)
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Human Tracking Using Distributed Vision Systems
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 1 - Volume 1
Multiple-View-Based Tracking of Multiple Humans
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 1 - Volume 1
Robust Tracking of Soccer Players Based on Data Fusion
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 1 - Volume 1
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 3
Multiple Camera Fusion for Multi-Object Tracking
WOMOT '01 Proceedings of the IEEE Workshop on Multi-Object Tracking (WOMOT'01)
Detecting Pedestrians Using Patterns of Motion and Appearance
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Recognizing Action at a Distance
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Real-time soccer player tracking method by utilizing shadow regions
Proceedings of the international conference on Multimedia
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Tracking objects that take part in sportive events is a challenging task because the objects move fast and occlusions occur frequently. When the tracked area is large, the use of more than one high resolution cameras improve accuracy, but leads to a huge amount of data to be processed and fused. The cameras are usually placed to maximize the covering area, and thus the tracked objects are small, usually 10 to 40 pixels height. This paper presents a new approach to this kind of application, where the tracking procedures are not applied to the whole images, but to small images taken from the cameras. Given a specific location of the tracked area, the system is able to return a set of small images (say 60x60 pixels) centered on that location, one from each camera, and the tracking procedures are applied to these images. Each object can be tracked individually by an independent module of the system, and each module can apply different tracking techniques depending on specific visual characteristics. The paper describes a real-time distributed implementation of such system, and presents a new mechanism to detect objects in small images using a gradient reference frame.