A multi-stage multi-candidate algorithm for motion estimation

T. C. Liao*, S. M. Phoong, Yuan-Pei Lin

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review


Motion compensation using the optimal full search algorithm is often too computational heavy for real time implementation. Many suboptimal fast search algorithms have been proposed. In particular, Liu and Zaccarin proposed the Alternating Subsampling Search Algorithm (ASSA). The ASSA reduces the computation by subsampling the pixels instead of limiting the search locations. It was shown that ASSA has nearly the same MSE performance as the full search but its complexity is only 1/4 of the full search. In this paper, we generalize the idea to the multi-stage case. Simulation results show that the proposed algorithm has a comparable performance to the ASSA but it has a much lower computational cost.

Original languageEnglish
Pages (from-to)1613-1616
Number of pages4
JournalICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
StatePublished - 26 Sep 2001
Event2001 IEEE Interntional Conference on Acoustics, Speech, and Signal Processing - Salt Lake, UT, United States
Duration: 7 May 200111 May 2001

Fingerprint Dive into the research topics of 'A multi-stage multi-candidate algorithm for motion estimation'. Together they form a unique fingerprint.

Cite this