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CVPR
2009
IEEE

Monitoring, Recognizing and Discovering Social Networks

10 years 5 months ago
Monitoring, Recognizing and Discovering Social Networks
This work addresses the important problem of the discovery and analysis of social networks from surveillance video. A computer vision approach to this problem is made possible by the proliferation of video data obtained from camera networks, particularly state-of-the-art Pan-Tilt-Zoom (PTZ) and tracking camera systems that have the capability to acquire high-resolution face images as well as tracks of people under challenging conditions. We perform “opportunistic” face recognition on captured images and compute motion similarities between tracks of people on the ground plane. To deal with the unknown correspondences between faces and tracks, we present a novel graph-cut based algorithm to solve this association problem. It enables the robust estimation of a social network that captures the interactions between individuals in spite of large amounts of noise in the datasets. We also introduce an algorithm that we call “modularity-cut”, which is an Eigen-analysis b...
Ting Yu, Ser Nam Lim, Kedar A. Patwardhan, Nils Kr
Added 09 May 2009
Updated 10 Dec 2009
Type Conference
Year 2009
Where CVPR
Authors Ting Yu, Ser Nam Lim, Kedar A. Patwardhan, Nils Krahnstoever
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