Please use this identifier to cite or link to this item:
http://hdl.handle.net/11375/9905
Title: | Implementation of a Multiple Frame Assignment Tracker in a CPU-GPU Integrated Environment |
Authors: | Herathkumar, K. |
Advisor: | Kirubarajan, T. |
Department: | Electrical and Computer Engineering |
Keywords: | Electrical and Computer Engineering;Electrical and Computer Engineering |
Publication Date: | Apr-2011 |
Abstract: | <p>The Multi Frame Assignment (MFA) tracker solves the data association problem as a constrained optimization for fusing multiple sets of data to the tracks with an Interacting Multiple Model (IMM) estimator.</p> <p>With the rapid development of parallel computing hardware such as GPU (Graphics Processor Unit) in recent years, GPGPU (General-Purpose computation on GPU) has become an important topic in scientific research applications. However, GPU might well be seen more as a cooperator than a rival to CPU. Therefore, exploiting the power of CPU and GPU in solving the MFA tracker algorithm based on CPU-GPG integrated computing environment is the focus of this thesis.</p> <p>In this thesis, a parallel MFA algorithm implementation based on CPU-GPU integrated computing model to optimize performance is presented. The results show that the algorithm increases the average performance by 10 times compared with the traditional algorithm. Based on the results and current trends in parallel computing architecture. it is believed that efficient use of CPU-GPU integrated environment will become increasingly important to high-performance tracking applications.</p> |
URI: | http://hdl.handle.net/11375/9905 |
Identifier: | opendissertations/4985 6007 2078799 |
Appears in Collections: | Open Access Dissertations and Theses |
Files in This Item:
File | Size | Format | |
---|---|---|---|
fulltext.pdf | 15.58 MB | Adobe PDF | View/Open |
Items in MacSphere are protected by copyright, with all rights reserved, unless otherwise indicated.