Continuous Multi-View Tracking using Tensor Voting

نویسندگان

  • Jinman Kang
  • Isaac Cohen
  • Gerard Medioni
چکیده

We present a novel approach for continuous tracking of moving objects observed by multiple fixed cameras. The continuous tracking of moving objects in each view is realized using a Tensor Voting based approach. We infer objects trajectories by performing a perceptual grouping in 2D+t. Gaps are bridged using a multi-scale approach in object trajectories. The trajectories obtained from the multiple cameras are registered in space and time allowing synchronization of the video streams and continuous tracking of objects across multiple views. We demonstrate the performance of the system on several real video surveillance sequences.

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تاریخ انتشار 2003