Multiple initial point prediction based search pattern selection for fast motion estimation

Nisar, Humaira; Choi, Tae‐Sun

doi:10.1016/j.patcog.2008.08.010

Cited by 15 publications

(2 citation statements)

References 20 publications

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“…The initial search centre prediction in [23] provided a notable reduction in computational cost and also improved matching efficiency. These methods are biased with the assumption that candidate block follows the same motion trajectory as their neighbouring blocks [24]. This assumption severely hits the matching accuracy for blocks located at the object boundaries, as these blocks may follow different motion trajectory than its neighbouring blocks.…”

Section: Introductionmentioning

confidence: 99%

Efficient direction‐oriented search algorithm for block motion estimation

Shinde

Tiwari

2018

IET Image Processing

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Section: Introductionmentioning

confidence: 99%

Efficient direction‐oriented search algorithm for block motion estimation

Shinde

Tiwari

2018

IET Image Processing

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“…Shen et al focus on adaptive and fast multi-frame selection algorithm to speed up the searching procedure for multiple reference frames [15]. Nisar et al proposed a robust scheme for initial motion vector prediction based spatial and temporal predictors [16].…”

Section: Introductionmentioning

confidence: 99%

Fast Macroblock Mode Selection Algorithm for B Frames in Multiview Video Coding

Yu¹,

He²,

Peng³

et al. 2011

KSII TIIS

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Intensive computational complexity is an obstacle of enabling multiview video coding for real-time applications. In this paper, we present a fast macroblock (MB) mode selection algorithm for B frames which are based on the computational complexity analyses between the MB mode selection and reference frame selection. Three strategies are proposed to reduce the coding complexity jointly. First, the temporal correlation of MB modes between current MB and its temporal corresponding MBs is utilized to reduce computational complexity in determining the optimal MB mode. Secondly, Lagrangian cost of SKIP mode is compared with that of Inter16×16 modes to early terminate the mode selection process. Thirdly, reference frame correlation among different Inter modes is exploited to reduce the number of reference frames. Experimental results show that the proposed algorithm can promote the encoding speed by 3.71~7.22 times with 0.08dB PSNR degradation and 2.03% bitrate increase on average compared with the joint multiview video model.

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Tracking of EEG Activity Using Motion Estimation to Understand Brain Wiring

Nisar

Malik

Ullah

et al. 2014

Signal and Image Analysis for Biomedical and Life Sciences

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The fundamental step in brain research deals with recording electroencephalogram (EEG) signals and then investigating the recorded signals quantitatively. Topographic EEG (visual spatial representation of EEG signal) is commonly referred to as brain topomaps or brain EEG maps. In this chapter, full search full search block motion estimation algorithm has been employed to track the brain activity in brain topomaps to understand the mechanism of brain wiring. The behavior of EEG topomaps is examined throughout a particular brain activation with respect to time. Motion vectors are used to track the brain activation over the scalp during the activation period. Using motion estimation it is possible to track the path from the starting point of activation to the final point of activation. Thus it is possible to track the path of a signal across various lobes.

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Multiple initial point prediction based search pattern selection for fast motion estimation

Cited by 15 publications

References 20 publications

Efficient direction‐oriented search algorithm for block motion estimation

Efficient direction‐oriented search algorithm for block motion estimation

Fast Macroblock Mode Selection Algorithm for B Frames in Multiview Video Coding

Tracking of EEG Activity Using Motion Estimation to Understand Brain Wiring

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