2009
DOI: 10.1007/978-3-642-00641-8_24
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FPGA-Based Anomalous Trajectory Detection Using SOFM

Abstract: Abstract. A system for automatically classifying the trajectory of a moving object in a scene as usual or suspicious is presented. The system uses an unsupervised neural network (Self Organising Feature Map) fully implemented on a reconfigurable hardware architecture (Field Programmable Gate Array) to cluster trajectories acquired over a period, in order to detect novel ones. First order motion information, including first order moving average smoothing, is generated from the 2D image coordinates (trajectories… Show more

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Cited by 6 publications
(4 citation statements)
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References 24 publications
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“…The system in [6] uses several digital signal processors on different PCI-boards, while the CITRIC [7] relies on the Intel XScale PXA270 processor. FP-GAs are used in systems such as [5] mostly as co-processor just for accelerating a single function. In [5] a Xilinx Spartan-3E FPGA is used as a co-processor.…”
Section: Related Workmentioning
confidence: 99%
See 1 more Smart Citation
“…The system in [6] uses several digital signal processors on different PCI-boards, while the CITRIC [7] relies on the Intel XScale PXA270 processor. FP-GAs are used in systems such as [5] mostly as co-processor just for accelerating a single function. In [5] a Xilinx Spartan-3E FPGA is used as a co-processor.…”
Section: Related Workmentioning
confidence: 99%
“…FP-GAs are used in systems such as [5] mostly as co-processor just for accelerating a single function. In [5] a Xilinx Spartan-3E FPGA is used as a co-processor. In [17], a hardware/software implementation on a Xilinx FPGA platform is presented for a 3D facial pose tracking application; the most-computationally intensive part is implemented in hardware while the remaining is implemented in the soft-core processors.…”
Section: Related Workmentioning
confidence: 99%
“…Reliability and security of reconfigurable systems must be ensured within a multiparty environment, and in critical applications, for example, aerospace and defence , telecoms [Hutchings et al 2002;Salefski and Caglar 2001], and surveillance [Appiah et al 2009;Mühlbauer and Bobda 2006;Ngo et al 2005].…”
Section: Introductionmentioning
confidence: 99%
“…Among them, concerning the studies for classifiers, e.g., [1]- [4] uses the technics of artificial neural networks. Another studies, e.g., [5]- [8] uses the other technics such as the AdaBoost algorithm, the wavelet transform and the nearest neighbor.…”
Section: Introductionmentioning
confidence: 99%