| 000 | 05333nam a2200541Ii 4500 | ||
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| 005 | 20250930140450.0 | ||
| 008 | 150410s2013 caua fobi 001 0 eng | ||
| 020 |
_z9781607051293 _qpapeback _cRM130.90 |
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| 020 | _a9781627051309 | ||
| 020 | _a1627051309 | ||
| 039 | 9 |
_a201507031602 _blan _c201507031559 _dlan _c201506181217 _drahah _y04-10-2015 _zrahah |
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| 040 |
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| 090 | _aTA1637.Z933 3 | ||
| 090 |
_aTA1637 _b.Z933 3 |
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| 100 | 1 |
_aZwart, Christine M. _eauthor. |
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| 245 | 1 | 0 |
_aControl grid motion estimation for efficient application of optical flow / _cChristine M. Zwart and David H. Frakes. |
| 264 | 4 | _c©2013. | |
| 264 | 1 |
_aSan Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA) : _bMorgan & Claypool, _c2013. |
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| 300 |
_a1 online resource (viii, 79 p.) : _billustrations ; _c24 cm. |
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| 336 |
_atext _2rdacontent |
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| 337 |
_acomputer _2rdamedia |
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| 338 |
_aonline resource _2rdacarrier |
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| 490 | 1 |
_aSynthesis lectures on algorithms and software in engineering, _x1938-1735 ; _v#11. |
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| 500 | _aPart of: Synthesis digital library of engineering and computer science. | ||
| 504 | _aIncludes bibliographical references : (p. 71-78). | ||
| 505 | 0 | _a1. Introduction -- 1.1 Registration and motion estimation -- 1.2 Block-based motion estimation -- 1.3 Optical flow -- 1.4 Conventions -- 1.5 Organization of the book -- | |
| 505 | 0 | _a2. Control grid interpolation (CGI) -- 2.1 Conventional CGI formulation -- 2.1.1 One-dimensional -- 2.1.2 Two-dimensional -- 2.2 Multiresolution and adaptive CGI formulations -- 2.3 Optimization mathematics -- 2.3.1 One-dimensional control grid and one degree of freedom optical flow -- 2.3.2 Two dimensional control grid and one degree of freedom optical flow -- 2.3.3 Two-dimensional control grid and two degrees of freedom optical flow -- 2.4 Symmetric implementations -- 2.5 Summary -- | |
| 505 | 0 | _a3. Application of CGI to registration problems -- 3.1 Registration of one-dimensional data: inter-vector registration -- 3.1.1 Dynamic timewarping -- 3.1.2 Isophote identification -- 3.2 Registration of two-dimensional data: inter-image registration -- 3.2.1 Motion estimation -- 3.2.2 Mitigation of atmospheric turbulence distortion -- 3.2.3 Medical image registration -- 3.3 Summary -- | |
| 505 | 0 | _a4. Application of CGI to interpolation problems -- 4.1 Interpolation of 1D data: inter-vector interpolation -- 4.1.1 Single-image super-resolution -- 4.1.2 Video deinterlacing -- 4.2 Interpolation of 2D data: inter-image interpolation -- 4.2.1 Inter-frame interpolation -- 4.2.2 Inter-slice interpolation -- 4.3 Summary -- | |
| 505 | 0 | _a5. Discussion and conclusions -- 5.1 Strengths and weaknesses -- 5.2 Application to higher-dimensions and multivariate optimization -- 5.3 Final thoughts and conclusions -- | |
| 505 | 0 | _aBibliography -- Authors' biographies. | |
| 506 | _aAbstract freely available; full-text restricted to subscribers or individual document purchasers. | ||
| 520 | 3 | _aMotion estimation is a long-standing cornerstone of image and video processing. Most notably, motion estimation serves as the foundation for many of today's ubiquitous video coding standards including H.264. Motion estimators also play key roles in countless other applications that serve the consumer, industrial, biomedical, and military sectors. Of the many available motion estimation techniques, optical flow is widely regarded as most flexible. The flexibility offered by optical flow is particularly useful for complex registration and interpolation problems, but comes at a considerable computational expense. As the volume and dimensionality of data that motion estimators are applied to continue to grow, that expense becomes more and more costly. Control grid motion estimators based on optical flow can accomplish motion estimation with flexibility similar to pure optical flow, but at a fraction of the computational expense. Control grid methods also offer the added benefit of representing motion far more compactly than pure optical flow. This booklet explores control grid motion estimation and provides implementations of the approach that apply to data of multiple dimensionalities. Important current applications of control grid methods including registration and interpolation are also developed. | |
| 650 | 0 | 0 |
_aImage processing _xDigital techniques. _959990 |
| 700 | 1 |
_aFrakes, David H. _q(David Harold), _d1976- _eauthor. |
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| 856 | 4 | 8 |
_3Abstract with links to full text _uhttp://dx.doi.org/10.2200/S00461ED1V01Y201212ASE011. |
| 856 | 4 | 0 |
_uhttp://oclc-marc.ebrary.com/Doc?id=10649982 _zAn electronic book accessible through the World Wide Web; click to view _3ebrary. |
| 856 | 4 | 0 |
_uhttp://site.ebrary.com/id/10649982 _3ebrary. |
| 856 | 4 | 0 |
_zAvailable by subscription from Safari Books Online _uhttp://proquest.safaribooksonline.com/?fpi=9781627051293. |
| 907 |
_a.b16118042 _b2025-07-18 _c2019-11-12 |
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| 914 | _avtls003583503 | ||
| 990 | _arab | ||
| 991 | _aFakulti Kejuruteraan dan Seni Bina | ||
| 998 |
_al _b2015-10-04 _cm _da _feng _gcau _y0 _z.b16118042 |
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