A Computationally Efficient Labeled Multi-Bernoulli Smoother for Multi-Target Tracking. [PDF]
Sensors (Basel), 2019 Liu R, Fan H, Li T, Xiao H.
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The Effect of Continuous Selection in KiwiCross® Composite Breed on Breed Ancestry and Productivity Performance. [PDF]
Animals (Basel)Jaafar M, Harris B, Huson HJ.
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Bacteria-Produced Algicide for Field Control of Toxic Dinoflagellates Does Not Cause a Cortisol Stress Response in Two Estuarine Fish Species. [PDF]
Mar Biotechnol (NY)Simons VE +3 more
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Consensus CPHD Filter for Distributed Multitarget Tracking
IEEE Journal on Selected Topics in Signal Processing, 2013 The paper addresses distributed multitarget tracking over a network of heterogeneous and geographically dispersed nodes with sensing, communication and processing capabilities. The contribution has been to develop a novel consensus Gaussian Mixture-Cardinalized Probability Hypothesis Density (GM-CPHD) filter that provides a fully distributed, scalable ...
Giorgio Battistelli +2 more
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An improved CPHD filter for unknown clutter backgrounds
Proceedings of SPIE, 2014 The “clutter-agnostic” CPHD filter was introduced at the 2010 SPIE Defense, Security and Sensing Symposium in 2010, and has been investigated in subsequent papers. This “κ-CPHD filter” was capable of multitarget detection and tracking in unknown, dynamically changing clutter backgrounds.
Ba-Ngu Võ
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An approximate CPHD filter for superpositional sensors
SPIE Proceedings, 2012 Most multitarget tracking algorithms, such as JPDA, MHT, and the PHD and CPHD filters, presume the following measurement model: (a) targets are point targets, (b) every target generates at most a single measurement, and (c) any measurement is generated by at most a single target.
Ronald Mahler, Adel El-Fallah
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Particle filter implementation of CPHD filter for unknown clutter
2017 6th International Conference on Electrical Engineering and Informatics (ICEEI), 2017In this paper, multitarget tracking in unknown clutter is studied. k-CPHD filter has been proposed by Mahler in 2010 on the basis of cardinalized probability hypothesis density (CPHD) filter. However, the researches about the implementation of k-CPHD filter are still scarce.
Xinglin Shen +2 more
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On CPHD filters with track labeling
SPIE Proceedings, 2017 The random infinite set (RFS) approach to information fusion addressed target track-labeling from the outset. The first implementations of RFS filters did not do so because of computational concerns, whereas subsequent implementations employed heuristics. The labeled RFS (LRFS) theory of B.-T. Vo and B.-N.
Mahler, Ronald, Ronald Mahler
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Adaptive genetic MM-CPHD filter for multitarget tracking
Soft Computing, 2016zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Bo Li 0059, Jianli Zhao, Fu-Wen Pang
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General solution and approximate implementation of the multisensor multitarget CPHD filter
2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2015Random finite set (RFS) based filters such as the cardinalized probability hypothesis density (CPHD) filter have been successfully applied to the problem of single sensor multitarget tracking. Various multisensor extensions of these filters have been proposed in the literature, but exact update equations for the multisensor CPHD filter have not been ...
Santosh Nannuru +2 more
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