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We consider a multiobject detection problem over a sensor network (SNET) with limited range multimodal sensors. The general problem complements the widely considered decentralized detection problem where all sensors observe the same object. We develop a distributed detection approach based on recent development of the false discovery rate (FDR) and the associated Benjamini-Hochberg (BH) procedure,...
In this paper we consider the problem of unsupervised topology reconstruction in uncalibrated visual sensor networks. We assume that a number of video cameras observe a common scene from arbitrary and unknown locations, orientations and zoom levels, and show that the extrinsic and calibration matrices, fundamental and essential matrices, the homography matrix, and the physical configuration of the...
We consider a change detection problem in video surveillance applications and propose busy-idle rates, meaningful and easy to compute features, to characterize the behavior profile of a given pixel. We describe the geometry independence property of these features, and use them to model the typical behavior that is observed in training sequences. Using a small number of samples for each pixel we generate...
In this work we consider two problems for video surveillance applications: (a) abnormal behavior detection and (b) behavior matching across cameras. We propose busy-idle rates, meaningful and easy to compute features of foreground objects, to characterize the behavior profile of a given pixel. We use these features to model the typical behavior that is observed in training sequences. Using a small...
Wireless sensor networks (SNET) have gained substantial interest for detection and localization of objects, however network energy constraints make it difficult to implement optimal solutions in distributed settings. For object localization with known power, maximum likelihood estimation is the optimal solution, however in many applications it involves performing optimization over a non-convex function,...
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