Distributed Signal Decorrelation and Detection in Multi View Camera Networks Using the Vector Sparse Matrix Transform

Leonardo R. Bachega, Srikanth Hariharan, Charles A. Bouman, Ness B. Shroff
2015 IEEE Transactions on Image Processing  
This paper introduces the vector sparse matrix transform (vector SMT), a new 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 outputs, until these vectors are decorrelated. In our experiments, we simulate distributed anomaly detection by a network of
more » ... meras monitoring a spatial region. Each camera records an image of the monitored environment from its particular viewpoint and outputs a vector encoding the image. Our results, with both artificial and real data, show that the proposed vector SMT transform effectively decorrelates image measurements from the multiple cameras in the network while maintaining low overall communication energy consumption. Since it enables joint processing of the multiple vector outputs, our method provides significant improvements to anomaly detection accuracy when compared to the baseline case when the images are processed independently.
doi:10.1109/tip.2015.2481709 pmid:26415179 fatcat:pffy2dhfbzfrliordms7hfky3u