Recursive Dynamically Variable Step Search Motion Estimation Algorithm for High Definition Video

Tasdizen, Ozgur; Hamzaoğlu, İlker

doi:10.1109/icpr.2010.576

Cited by 2 publications

(3 citation statements)

References 12 publications

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“…Considering the recently available consumer electronics devices such as HD digital video broadcasting [7], this is an evidence that ME in HD may become a central issue in the forthcoming years. To the best of our knowledge, there is a paucity of results about this issue, which requires further research.…”

Section: A Me In High Definitionmentioning

confidence: 98%

“…In [7] the Recursive Dynamically Variable Step Search (RDVSS) ME algorithm for real-time processing of HD video formats is proposed. This algorithm is an improvement over the DVSS algorithm and it dynamically determines the search patterns that will be used for each block based on the MVs of its spatial and temporal neighboring blocks.…”

Section: B Related Workmentioning

confidence: 99%

“…cell phones, all these algorithms perform well provided that, in this context, fast and complex motion tends to be infrequently [7]. In this paper, we will present two novel algorithms for motion estimation in High Definition (HD) which were specifically designed to achieve high quality in this context while enjoying comparable computational complexity of fast algorithms previously developed.…”

Section: Introductionmentioning

confidence: 98%

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Two Novel Algorithms for High Quality Motion Estimation in High Definition Video Sequences

Noble

Porto

Agostini

et al. 2011

2011 24th SIBGRAPI Conference on Graphics, Patterns and Images

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In this paper, we propose two new algorithms for high quality motion estimation in high definition digital videos. Both algorithms are based on the use of random features that guarantee robustness to avoid dropping into a local-minimum. The first algorithm was developed from a simple two stage approach where a random stage is complemented by a greedy stage in a very simple fashion. The second algorithm is based on a more refined class of algorithms called Memetic Network Algorithms where each instance of the search may exchange information with its neighbour instances according to some rules that control the information flow. The proposed algorithms were implemented and tested exclusively with high definition sequences against well known fast algorithms like Diamond Search and Three Step Search. The results show that our algorithms can outperform other algorithms in quality yielding an increment in complexity that may be amortized if resources for a parallel execution are available. Additionally, we provide further evidence that fast algorithms do not perform well in high definition.

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Section: A Me In High Definitionmentioning

confidence: 98%

Section: B Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 98%

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