Monitoring Activities from Multiple Video Streams: Establishing a Common Coordinate Frame
IEEE Transactions on Pattern Analysis and Machine Intelligence
VS '99 Proceedings of the Second IEEE Workshop on Visual Surveillance
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
Image Mosaicing and Super-Resolution (Cphc/Bcs Distinguished Dissertations.)
Image Mosaicing and Super-Resolution (Cphc/Bcs Distinguished Dissertations.)
Multi-views tracking within and across uncalibrated camera streams
IWVS '03 First ACM SIGMM international workshop on Video surveillance
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Histograms of Oriented Gradients for Human Detection
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
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Correspondence between distributed cameras with overlapping views is needed for several tasks in surveillance and smart environments. This paper proposes an adaptive correspondence estimation technique by observing multiple humans in a planar scene. In contrast to other RANSAC-based approaches, it does not require prior information about corresponding features. The proposed techniques uses only results from a person detector and scene specific detection filtering for estimating the inter-image homography. The method is self-configurable, adaptive and provides robustness over time by exploiting temporal and geometric constraints. The correspondence is accurately estimated in spite of error sources such as missed detections, false detections and non overlapping fields of view. Results on a variety of datasets demonstrate the general applicability. Experiments show that the proposed correspondence estimation approach outperforms a common baseline approach.