Small-diamond-based search algorithm for fast block motion estimation

Tai, Shen-Chuan; Chen, Ying-Ru; Chen, Yu-Hung

doi:10.1016/j.image.2007.07.004

Cited by 10 publications

(3 citation statements)

References 14 publications

(17 reference statements)

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“…Since most of the block model is 16 × 16 and 8 × 8, set two thresholds to predict the 16 × 16 and 8 × 8 of the stationary block. These two thresholds can ensure that it can reduce the computations but does not affect the accuracy of motion estimation [9][10].…”

Section: A Stationary Block Predictionmentioning

confidence: 99%

An Efficient Motion Estimation Algorithm for H.264/AVC

Zhang

2013

AMM

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The efficient motion estimation algorithms are the important research hotspot in the real-time video coding-decoding technology. This paper proposes a novel and simple fast motion estimation algorithm based on adaptive search-pattern. The new algorithm includes three schemes: stationary block prediction, predictive search for non-stationary blocks, choosing a starting point and adaptive refinement search in merging process. Experiments show that the efficient motion estimation algorithm proposed can further reduce the computations of block-matching while improve the compression effect.

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Section: A Stationary Block Predictionmentioning

confidence: 99%

An Efficient Motion Estimation Algorithm for H.264/AVC

Zhang

2013

AMM

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“…2 (a) and the small cross search pattern (SCSP) in Fig. 2 (b) to improve the diamond search algorithm [7,8]. Firstly, we search the MBD point in the 9 points in these two patterns.…”

Section: A Diamond Search Block-matching Algorithmmentioning

confidence: 99%

Human Activity Recognition Based on Improved Diamond Search Block-Matching Method

Yin

2011

2011 Fourth International Symposium on Computational Intelligence and Design

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A novel method to recognize human activities based on videos is proposed in this paper. These videos are captured by a camera mounted to a human body. We can estimate the activity from the changes of scenes in videos. In this paper, we use the improved diamond search block-matching method to calculate the motion vector. Then we extract key information from the motion vector filed, and design a feature descriptor to describe the motion in frames in a video which can distinguish different motions. After getting feature descriptors, we use SVM classifier to classify different motions with a machine learning method. Experimental results show that our method successfully identifies simple motion such as walking, running, going upstairs and going downstairs. And the block size and the frequency of videos have impacts on classification precision.

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“…To reduce the extremely high complexity of the FSBM, many halfway-stop fast algorithms for computing motion estimation have been proposed, such as "three-step search (3SS)," "new three step search (N3SS)," 9 "four-step search (4SS)," 10 "diamond search (DS)," 11 "cross diamond search (CDS)," 12 "hexagon-base search (HEXBS)," 13 "smalldiamond-based search," 14 "new cross-hexagon search" (NCHEXS), 15 "search patterns switching (SPS)," 16 and "hardware-oriented modified diamond search (HMDS)." 17 Such algorithms reduce computational complexity by limiting the number of search points within the search range.…”

Section: Introductionmentioning

confidence: 99%

Content-adaptive thresholding early termination scheme on directional gradient descent searches for fast block motion estimation

Chen

Lin

et al. 2012

Opt. Eng

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An efficient algorithm named modified directional gradient descent searches to enhance the directional gradient descent search (DGDS) algorithm is presented to reduce computations. A modified search pattern with an adaptive threshold for early termination is applied to DGDS to avoid meaningless calculation after the searching point is good enough. A statistical analysis of best motion vector distribution is analyzed to decide the modified search pattern. Then a statistical model based on the characteristics of the block distortion information of the previous coded frame helps the early termination parameters selection, and a trade-off between the video quality and the computational complexity can be obtained. The simulation results show the proposed algorithm provides significant improvement in reducing the motion estimation (ME) by 17.81% of the average search points and 20% of ME time saving compared to the fast DGDS algorithm implemented in H.264/AVC JM 18.2 reference software according to different types of sequences, while maintaining a similar bit rate without losing picture quality.

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Small-diamond-based search algorithm for fast block motion estimation

Cited by 10 publications

References 14 publications

An Efficient Motion Estimation Algorithm for H.264/AVC

An Efficient Motion Estimation Algorithm for H.264/AVC

Human Activity Recognition Based on Improved Diamond Search Block-Matching Method

Content-adaptive thresholding early termination scheme on directional gradient descent searches for fast block motion estimation

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