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A diffusion framework for detection of moving A. Averbuch, K. Hochman, N. Rabin, A. Schclar and V. Zheludev
 

Summary: A diffusion framework for detection of moving
vehicles
A. Averbuch, K. Hochman, N. Rabin, A. Schclar and V. Zheludev
School of Computer Science
Tel Aviv University, Tel Aviv 69978, Israel
Abstract
Automatic acoustic-based vehicle detection is a common task in se-
curity and surveillance systems. Usually, a recording device is placed
in a designated area and a hardware/software system processes the
sounds that are intercepted by this recording device to identify vehicles
only as they pass by. We propose a novel algorithm for the real-time
detection of vehicles based on their recordings. The algorithm uses the
wavelet-packet transform in order to extract spatio-temporal charac-
teristic features from the recordings where the underlying assumption
is that these features constitute a unique acoustic signature for each
of the recordings. The feature extraction procedure is followed by the
Diffusion Maps (DM) dimensionality reduction algorithm which fur-
ther reduces the size of the signature. A new recording is classified
1
by employing the wavelet-packet feature extraction and embedding

  

Source: Averbuch, Amir - School of Computer Science, Tel Aviv University

 

Collections: Computer Technologies and Information Sciences