Particle Filters for Object Tracking: Enhanced Algorithm and Efficient Implementations - Softcover

Abd El-Halym, Howida; Ismail Mahmoud, Imbaby; El-Din Habib, Serag

Softcover

ISBN 10: 3659243485 ISBN 13: 9783659243486

Publisher: LAP LAMBERT Academic Publishing, 2013

Synopsis

Particle filters are advanced for building robust object trackers capable of operation under difficult tracking conditions. An Excitation Particle Filter (EPF) is introduced in this book for object tracking. A new likelihood model is proposed. It depends on multiple likelihood functions: position likelihood; gray level intensity likelihood and similarity likelihood. Also, we modify the PF as a robust estimator to overcome the well-known sample impoverishment problem of the PF. The proposed enhanced PF (EPF) is implemented in software and evaluated. Simulation results demonstrated the superior performance of the proposed tracker in terms of accuracy, robustness and occlusion over classical tracking algorithms. Three efficient novel hardware architectures of the Sample Important Resample Filter (SIRF) and the EPF are introduced and implemented on FPGA platform. These architectures feature speed improvement, efficient memory utilization, and/or hardware resource saving.

About this title

About the Author

Lecturer at Department of Computers and Systems Engineering , Faculty of Engineering, Zagazig University. Lecturer at Nuclear Research Center. PhD. and Msc. in Electronic and Communication from Faculty of Engineering, Cairo University 2010 and 2002. Bsc. in Electronic and Communication from Faculty of Engineering, Zagazig University 1993.

Edition details

• Publisher: LAP LAMBERT Academic Publishing
• Publication date: 2013
• Language: English
• ISBN 10: 3659243485
• ISBN 13: 9783659243486
• Binding: Paperback
• Number of pages: 120