Synthetic Aperture Tracking: Tracking through Occlusions

  • ,
  • Shai Avidan ,
  • Wojciech Matusik ,
  • David J. Kriegman

Computer Vision, 2007. ICCV 2007. IEEE 11th International Conference on |

Published by IEEE

Publication | Publication

Occlusion is a significant challenge for many tracking algorithms. Most current methods can track through transient occlusion, but cannot handle significant extended occlusion when the object’s trajectory may change significantly. We present a method to track a 3D object through significant occlusion using multiple nearby cameras (e.g., a camera array). When an occluder and object are at different depths, different parts of the object are visible or occluded in each view due to parallax. By aggregating across these views, the method can track even when any individual camera observes very little of the target object. Implementation- wise, the methods are straightforward and build upon established single-camera algorithms. They do not require explicit modeling or reconstruction of the scene and enable tracking in complex, dynamic scenes with moving cameras. Analysis of accuracy and robustness shows that these methods are successful when upwards of ‘70% of the object is occluded in every camera view. To the best of our knowledge, this system is the first capable of tracking in the presence of such significant occlusion.

Synthetic Aperture Tracking: Tracking through Occlusions

Occlusion is a significant challenge for many tracking algorithms. Most current methods can track through transient occlusion, but cannot handle significant extended occlusion when the object's trajectory may change significantly. We present a method to track a 3D object through significant occlusion using multiple nearby cameras (e.g., a camera array). When an occluder and object are at different depths, different parts of the object are visible or occluded in each view due to parallax. By aggregating across these views, the method can track even when any individual camera observes very little of the target object. Implementation- wise, the methods are straightforward and build upon established single-camera algorithms. They do not require explicit modeling or reconstruction of the scene and enable tracking in complex, dynamic scenes…