DocumentCode
2987672
Title
The cost of data dependence in motion vector estimation for reconfigurable platforms
Author
Ang, Su-Shin ; Constantinides, George ; Luk, Wayne ; Cheung, Peter
Author_Institution
Dept. of Electr. & Electron. Eng., Imperial Coll., London
fYear
2006
fDate
Dec. 2006
Firstpage
333
Lastpage
336
Abstract
Motion vector estimation is frequently performed as a prelude to the exploitation of temporal redundancies in video applications. As a result, a large volume of work has been done to develop techniques to avoid the heavy memory access requirements of full search motion vector estimation. Often, these approaches introduce data dependence to the algorithm, leading to memory accesses which cannot be determined at design time. Consequently, this complicates the exploitation of data reuse in hardware. In this work, the cost of data dependence is quantified. Experiments indicate that a data dependent fast motion vector estimation approach is faster than full search by up to 47% in the absence of data re-use optimisation. However, full search is approximately 16 times faster than the `fast´ motion vector estimation algorithm when a static line buffering scheme and a parallel caching scheme are used respectively to exploit data re-use. Therefore, it is established that data dependence in motion vector estimation is very expensive in terms of hardware performance
Keywords
field programmable gate arrays; motion estimation; data dependence cost; motion vector estimation; reconfigurable platforms; temporal redundancy; video applications; Algorithm design and analysis; Communication standards; Costs; Data engineering; Educational institutions; Embedded system; Field programmable gate arrays; Hardware; Motion estimation; Quality of service;
fLanguage
English
Publisher
ieee
Conference_Titel
Field Programmable Technology, 2006. FPT 2006. IEEE International Conference on
Conference_Location
Bangkok
Print_ISBN
0-7803-9729-0
Electronic_ISBN
0-7803-9729-0
Type
conf
DOI
10.1109/FPT.2006.270341
Filename
4042463
Link To Document