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Motion vectors in most practical encoders are selected by conventional motion estimation methods, using simplified Lagrangian cost function[6].
Figure 2 shows the estimated motion vector fields for the Grove sequence using the three aforementioned motion estimation methods.
One approach to performing motion estimation on synthetic animations is to treat them as video sequences and use standard image-based motion estimation methods.
First, the complexity of full and fast motion estimation methods is modeled in an implementation and platform independent manner.
The proposed method was compared with several existing motion estimation methods via a series of experiments with synthetic speckle image sequences.
Fully automated motion estimation methods were performed in post-processing to correct for the inter- and intra-frame motion in SLO images and their concurrently acquired OCT volumes.
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The muscular architecture dynamics is captured in ultrasonography sequences and estimated using a previously reported motion estimation method.
This study also proposes a computation-aware motion estimation method for the H.264/AVC.
An arm motion estimation method is designed based on the fuzzy predictive control theory.
We present a very efficient parametric motion estimation method, where most computation can be done offline.
Based on this analysis, we propose a motion estimation method in the DCT domain, and we show that results comparable to standard block matching can be obtained.
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