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The paper presents an approach for tracking a variable number of objects by using a multi-layer particle filter combined with an extended Expectation Maximization (EM) clustering. The approach works on basis of binary foreground images coming from previous background subtraction. The multi-layer particle filter is an improvement of a conventional particle filter approach. It uses an introduced adaptive...
This paper investigates the box-particle filter for multi-target tracking, and proposes a clustering based box-particle implementation of PHD filter. A subdivision step is added before the estimation of states. Each box is divided into several sub-box based on the estimated number of targets. An equivalent set of particles can be extracted from the set of subdivided boxes. Then, clustering technique...
Recent work on distributed algorithms for Sensor Allocation and Management has focused on heuristic methods to address the challenges posed by limited processing and communication resources. Heuristic methods tend to have good real-time performance, but are often lacking in system optimality. This paper explores the tradeoff by proposing a spectrum of algorithms starting with centralized math programming...
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