Activity based matching in distributed camera networks

  • Authors:
  • Erhan Baki Ermis;Pierre Clarot;Pierre-Marc Jodoin;Venkatesh Saligrama

  • Affiliations:
  • Boston University, Boston, MA;Université de Sherbrooke Sherbrooke, QC, Canada;Université de Sherbrooke Sherbrooke, QC, Canada;Boston University, Boston, MA

  • Venue:
  • IEEE Transactions on Image Processing - Special section on distributed camera networks: sensing, processing, communication, and implementation
  • Year:
  • 2010

Quantified Score

Hi-index 0.00

Visualization

Abstract

In this paper, we consider the problem of finding correspondences between distributed cameras that have partially overlapping field of views. When multiple cameras with adaptable orientations and zooms are deployed, as in many wide area surveillance applications, identifying correspondence between different activities becomes a fundamental issue. We propose a correspondence method based upon activity features that, unlike photometric features, have certain geometry independence properties. The proposed method is robust to pose, illumination and geometric effects, unsupervised (does not require any calibration objects). In addition, these features are amenable to low communication bandwidth and distributed network applications. We present quantitative and qualitative results with synthetic and real life examples, and compare the proposed method with scale invariant feature transform (SIFT) based method. We show that our method significantly outperforms the SIFT method when cameras have significantly different odentations. We then describe extensions of our method in a number of directions including topology reconstruction, camera calibration, and distributed anomaly detection.