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Motion estimation

It is conceivable that the equilibrium orientation of the intercalated dye in its Sj excited state differs from that in its S0 ground state and that this is what is responsible for the rapid initial relaxation. If so, the rms amplitudes of internal Brownian motion estimated above would be upper limits to the actual values. [Pg.176]

Parameters corrected for librational motion. Estimated standard deviations are 0.0004 and 0.0005 A for the uncorrected bond lengths, 0.03 and 0.04° for the angles. [Pg.153]

Numbers in parantheses indicate standard deviations >) Distance corrected for thermal motion ) Estimate and not a... [Pg.170]

For the simple shear flow of Problem 4.5, determine the dispersion coefficient by following Taylor s general approach. Neglect molecular diffusion in the direction of motion. Estimate the times, analytically and numerically, for which any approximations used in your analysis are valid, and the times for which diffusion in the direction of motion can be neglected. [Pg.135]

Quiet, easy hum of a motor. Tap tap tap of feet on a hard floor—an audio discrimination program went primary— two sets of feet, plus the level breathing of two people. Constant pulse of light pressure on the enhanced retinas below closed eyelids indicated linear movement, backed up by inner ear fluid motion estimated at a fast walking pace. Posture was level he was still lying on his bed. [Pg.320]

Besides, let s add to this analysis the characteristic times of the segmental motion, estimated based on coefficient of the frictional component of viscosity of diluted solution ), concentrated solution and melt ( ). [Pg.163]

Parallel to, and often independent of, the correspondence-based approach, optical flow-based structure and motion estimation algorithms have flourished for more than two decades. Although robust dense optical flow estimates are still elusive, the field has matured to the extent that systematic characterization and evaluation of optical flow estimates are now possible. Methods that use robust statistics, generalized motion models, and filters have all shown great promise. Significant work that uses directly observable flow ( normal flow ) provides additional insight into the limitations of traditional approaches. An example of depth estimation using optical flow is shown in Fig. 8. [Pg.157]

An approximate but effective algorithm to compress video signals uses the idea of motion estimation (ME) [9]. In this algorithm, the position of a small part of the current frame in the previous image-frame is searched, i.e., one tries to determine the motion of part of the image between consecutive frames. Only the motion vector is then transmitted instead of all the pixels. This results in a significant compression of the video signal. [Pg.121]

The design of an architecture for this motion estimation application, using the tuned design script of figure 1, is presented in the following sections. It illustrates the individual steps for which a short summary of and a reference to the applied synthesis techniques are supplied. [Pg.122]

Based on the denotational semantics of Alpha [11], axiomatic rules are defined, and semantic-preserving transformations oriented towards the synthesis of systolic arrays are built from these rules. The Alpha du Centaur program offers an interactive environment for applying these transformations, either for the generation of a parallel program [8] or for the synthesis of a chip [2]. A few of these transformations will be discussed in more depth for the motion estimator below. [Pg.123]

Figure 8 The undecorated localization graph for the motion estimation application. Figure 8 The undecorated localization graph for the motion estimation application.
Figure 10 Final architecture for the motion estimation cilgorithm. Figure 10 Final architecture for the motion estimation cilgorithm.
The example design of a motion estimation application using the design script resulted in an architecture that can be compared with even the best manual designs. The careful selection of the transformation matrix produced an architecture with optimal I/O and control flow. Only control logic and I/O at the borders is needed, and the interface buffer sizes needed are very small. This shows that the proposed methodology and tools can indeed be used for complex real-life examples, with optimal results. [Pg.140]

J. Rosseel, F. Catthoor, and H. De Man. The systematic design of a motion estimation array architecture. Proc. of the IEEE International Conference on Application Specific Array Processors, pages 40-54. IEEE Computer Society Press, 1991. [Pg.142]

T. Ortmaier, M. Groger, D. H. Boehm, V. Falk, and G. Hirzinger, "Motion estimation in beating heart surgery," IEEE Trans. Biomed. Eng, 52(10) 1729-1740, October, 2005. [Pg.89]

As a result, the association and temporal smoothing of the detections has the additional benefit that a temporal track of vehicle detentions is built up (see blue boxes in Fig. 6). This 2D track is utilized for the linear motion estimate which is... [Pg.493]

Gasperis, G. Wang, X. Yang, J. Becker, F. and Gascoyne, P. (1998), Automated electrorotation dielectric characterization of living cells by real-time motion estimation, Measurement Science and Technology 9, 518. [Pg.585]

Motion estimation is a process to determine the motion vector in a video sequences by reducing temporal redundancy between consecutive successful video frames [1, 2], Motion estimation identifies blocks that match each other in a video sequences by detecting objects transformation which appears in each frames but at different locations [3], The identified blocks will be represented with a motion vector (x, y) to indicate the motion pixel displacement in frames [4], Differences of values in pixels indicate that there are changes occurred in the frames. Block Matching Algorithm (BMA) technique is widely used for motion estimation where a frame is divided into square size of macro blocks [5, 6], The pixels values of the macro blocks which are divided will be used to compare between current macro block with the subsequent macro block [7, 8, 9] in the same frame. [Pg.690]

To evaluate the changes of pixels values of a small macro block between targeted frames (video sequences) in order to determine motion estimation, each of the interested frames is divided into 8x8 small macro block as illustrated in Fig. 1. [Pg.690]

Ahluwalia S, Dr. Shukla A, Rungta S (2010) Optimal Circular 2-D Search Algorithm for Motion Estimation, Intmiational Multi Conference of Engineers and Computo" Scientists 2010 vol E, Hong Kong... [Pg.693]

Prabhudev f Hosur, Ma K K (1999) Motion Vecto" Field Adaptive Fast Motion Estimation, 2nd Intmiational Conference Information, Communications and Signal Processing Singapore... [Pg.693]

Chen X, Zhao Z, Rahmati A, et al. (2009) SaVE Senso -assisted Motion Estimation for Efficient H.264/AVC Video Encoding, ACM Multimedia, Beijing, China... [Pg.693]

Hiadtare M (2007) Motion Estimation Techniques in Video Processing, Electronic Engineering Times India, India... [Pg.693]

Ishfaq A, Weiguo Z, Jiancong L, Ming L, (2006) A Fast Adaptive Motion Estimation Algorithm, IEEE Transactions on Circuits and Systems for Video Technology, vol.l6, no.3... [Pg.693]

Ranjit S, Sim K S, Besar R, Tso C P (2008) Motion Estimation in Medical Imaging, 4" Kuala Lumpur International Conference on Biomedical Engineering, pp 603-606... [Pg.693]

Pulido N, Ojeda A, Atakan K, Kubo T (2004) Strong ground motion estimation in the Marmara Sea region (Turkey) based on a scenario earthquake. Tectonophysics 391 357-374... [Pg.1833]

Zhu X, Bamler R (2011) Let s do the time warp multicomponent nonlinear motion estimation in differential SAR tomography. IEEE Geosci Remote Sens Lett 8 735-739... [Pg.2450]


See other pages where Motion estimation is mentioned: [Pg.114]    [Pg.76]    [Pg.222]    [Pg.19]    [Pg.158]    [Pg.17]    [Pg.119]    [Pg.1480]    [Pg.1892]    [Pg.50]    [Pg.203]    [Pg.244]    [Pg.457]    [Pg.487]    [Pg.508]    [Pg.690]    [Pg.389]    [Pg.245]    [Pg.1984]   
See also in sourсe #XX -- [ Pg.121 ]




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Example motion estimation

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