Name
Title | ||
|---|---|---|
Distributed vector decorrelation and anomaly detection using the vector Sparse Matrix Transform |
Abstract | ||
|---|---|---|
Here, we propose the vector Sparse Matrix Transform (SMT), a novel decorrelating transform suitable for performing distributed processing of high dimensional signals in sensor networks. We assume that each sensor in the network encodes its measurements into vector outputs instead of scalar ones. The proposed transform decorrelates a sequence of pairs of vector sensor outputs, until these vectors are decorrelated. In our experiments, we simulate distributed anomaly detection by a camera network monitoring a spatial region. Each camera records an image of the monitored environment from its particular viewpoint and outputs a vector encoding the image. Results show that the vector SMT effectively decorrelates images from the multiple cameras in the network and significantly improves anomaly detection accuracy while requiring low overall communication energy. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/ICASSP.2014.6854233 | Acoustics, Speech and Signal Processing |
Keywords | Field | DocType |
covariance matrices,decorrelation,distributed processing,sparse matrices,decorrelating transform,distributed anomaly detection,distributed processing,distributed vector decorrelation,high dimensional signals,multiple cameras,sensor networks,vector sparse matrix transform | Anomaly detection,Computer vision,Decorrelation,Pattern recognition,Computer science,Scalar (physics),Camera network,Vector sensor,Artificial intelligence,Wireless sensor network,Sparse matrix,Encoding (memory) | Conference |
ISSN | Citations | PageRank |
1520-6149 | 1 | 0.35 |
References | Authors | |
13 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Leonardo R. Bachega | 1 | 87 | 11.25 |
| Charles A. Bouman | 2 | 2740 | 473.62 |