Joint acoustic-video fingerprinting of vehicles, part II

In this second paper, we first show how to estimate the wheelbase length of a vehicle using line metrology in video. We then address the vehicle fingerprinting problem using vehicle silhouettes and color invariants. We combine the acoustic metrology and classification results discussed in Part I with the video results to improve estimation performance and robustness. The acoustic video fusion is achieved in a Bayesian framework by assuming conditional independence of the observations of each modality. For the metrology density functions, Laplacian approximations are used for computational efficiency. Experimental results are given using field data.


Presented at:
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Honolulu, HI, Apr 15-20, 2007
Year:
2007
Keywords:
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 Record created 2010-09-07, last modified 2018-03-17

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