Dissertations / Theses on the topic 'Motion Estimation'
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Cheng, Xin. "Feature-based motion estimation and motion segmentation." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape7/PQDD_0016/MQ55493.pdf.
Full textJaganathan, Venkata Krishnan. "Robust motion estimation techniques." Diss., Columbia, Mo. : University of Missouri-Columbia, 2007. http://hdl.handle.net/10355/6032.
Full textThe entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file (viewed on April 15, 2008) Includes bibliographical references.
Rekleitis, Ioannis. "Visual motion estimation based on motion blur interpretation." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1996. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/MQ44103.pdf.
Full textRekleitis, Ioannis. "Visual motion estimation based on motion blur interpretation." Thesis, McGill University, 1995. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=20154.
Full textAy, Emre. "Ego-Motion Estimation of Drones." Thesis, KTH, Robotik, perception och lärande, RPL, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-210772.
Full textFör att avlägsna behovet av extern infrastruktur så som GPS, som dessutominte är tillgänglig i många miljöer, är det önskvärt att uppskatta en drönares rörelse med sensor ombord. Visuella positioneringssystem har studerats under lång tid och litteraturen på området är ymnig. Syftet med detta projekt är att undersöka de för närvarande tillgängliga metodernaoch designa ett visuellt baserat positioneringssystem för drönare. Det resulterande systemet utvärderas och visas ge acceptabla positionsuppskattningar.
Wu, Siu Fan. "General motion estimation and segmentation." Thesis, University of Surrey, 1990. http://epubs.surrey.ac.uk/843155/.
Full textFakhouri, Elie Michel. "Variable block-size motion estimation." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp01/MQ37260.pdf.
Full textMok, Wai-hung Toby, and 莫偉雄. "Motion estimation in feature domain." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2000. http://hub.hku.hk/bib/B31223230.
Full textZayas-Cedeño, Gricelis 1974. "Motion estimation of cloud images." Thesis, Massachusetts Institute of Technology, 1998. http://hdl.handle.net/1721.1/50035.
Full textIncludes bibliographical references (leaves 63-64).
by Gricelis Zayas-Cedeño.
M.S.
Weiss, Yair. "Bayesian motion estimation and segmentation." Thesis, Massachusetts Institute of Technology, 1998. http://hdl.handle.net/1721.1/9354.
Full textIncludes bibliographical references (leaves 195-204).
Estimating motion in scenes containing multiple moving objects remains a difficult problem in computer vision yet is solved effortlessly by humans. In this thesis we present a computational investigation of this astonishing performance in human vision. The method we use throughout is to formulate a small number of assumptions and see the extent to which the optimal interpretation given these assumptions corresponds to the human percept. For scenes containing a single motion we show that a wide range of previously published results are predicted by a Bayesian model that finds the most probable velocity field assuming that (1) images may be noisy and (2) velocity fields are likely to be slow and smooth. The predictions agree qualitatively, and are often in remarkable agreement quantitatively. For scenes containing multiple motions we introduce the notion of "smoothness in layers". The scene is assumed to be composed of a small number of surfaces or layers, and the motion of each layer is assumed to be slow and smooth. We again formalize these assumptions in a Bayesian framework and use the statistical technique of mixture estimation to find the predicted a surprisingly wide range of previously published results that are predicted with these simple assumptions. We discuss the shortcomings of these assumptions and show how additional assumptions can be incorporated into the same framework. Taken together, the first two parts of the thesis suggest that a seemingly complex set of illusions in human motion perception may arise from a single computational strategy that is optimal under reasonable assumptions.
(cont.) The third part of the thesis presents a computer vision algorithm that is based on the same assumptions. We compare the approach to recent developments in motion segmentation and illustrate its performance on real and synthetic image sequences.
by Yair Weiss.
Ph.D.
Magarey, Julian. "Motion estimation using complex wavelets." Thesis, University of Cambridge, 1997. https://www.repository.cam.ac.uk/handle/1810/273016.
Full textXie, Liguang. "Realistic Motion Estimation Using Accelerometers." Thesis, Virginia Tech, 2009. http://hdl.handle.net/10919/43368.
Full textMaster of Science
Dérian, Pierre. "Wavelets and Fluid Motion Estimation." Rennes 1, 2012. https://ecm.univ-rennes1.fr/nuxeo/site/esupversions/5cdcde8f-715b-4725-a6d4-4eea6474aead.
Full textThis work falls within the general problematic of designing measurement tools adapted to the specificities of fluid flows. The development of digital imaging, combined with visualization techniques commonly employed in experimental fluid dynamics, enables to extract the apparent flow motion from image sequences, thanks to computer vision methods. The objective is to propose a novel “optical flow” algorithm dedicated to the multiscale motion estimation of fluid flows, using a wavelet representation of the unknown motion field. This wavelet formulation introduces a multiscale framework, conveniently adapted both to the optical flow estimation and to the representation of turbulent motion fields. It enables as well to design divergence-free bases, thereby respecting a constraint given by fluid dynamics. Several regularization schemes are proposed; the simplest consists in truncating the basis at fine scales, while the most complex builds high-order schemes from the connection coefficients of the wavelet basis. Proposed methods are evaluated on synthetic images in the first place, then on actual experimental images of characteristic fluid flows. Results are compared to those given by the usual “cross-correlations”, highlighting the advantages and limits of the wavelet-based estimator
Fu, Ming Fai. "Motion estimation and compensation in wavelet domain and fast global motion estimation for video coding /." View Abstract or Full-Text, 2002. http://library.ust.hk/cgi/db/thesis.pl?ELEC%202002%20FU.
Full textIncludes bibliographical references (leaves 98-102). Also available in electronic version. Access restricted to campus users.
Reza-Alikhani, Hamid-Reza. "Motion compensation for image compression : pel-recursive motion estimation algorithm." Thesis, Loughborough University, 2002. https://dspace.lboro.ac.uk/2134/33721.
Full textBalfour, Daniel Robert Malcolm. "Reduced-parameter motion estimation in PET using respiratory motion models." Thesis, King's College London (University of London), 2017. https://kclpure.kcl.ac.uk/portal/en/theses/reducedparameter-motion-estimation-in-pet-using-respiratory-motion-models(78899c82-9fb3-4fe7-b319-70c3be304a0e).html.
Full textHemmendorff, Magnus. "Single and Multiple Motion Field Estimation." Licentiate thesis, Linköping University, Linköping University, Computer Vision, 1999. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-54343.
Full textThis thesis presents a framework for estimation of motion fields both for single and multiple layers. All the methods have in common that they generate or use constraints on the local motion. Motion constraints are represented by vectors whose directions describe one component of the local motion and whose magnitude indicate confidence.
Two novel methods for estimating these motion constraints are presented. Both methods take two images as input and apply orientation sensitive quadrature filters. One method is similar to a gradient method applied on the phase from the complex filter outputs. The other method is based on novel results using canonical correlation presented in this thesis.
Parametric models, e.g. affine or FEM, are used to estimate motion from constraints on local motion. In order to estimate smooth fields for models with many parameters, cost functions on deformations are introduced.
Motions of transparent multiple layers are estimated by implicit or explicit clustering of motion constraints into groups. General issues and difficulties in analysis of multiple motions are described. An extension of the known EM algorithm is presented together with experimental results on multiple transparent layers with affine motions. Good accuracy in estimation allows reconstruction of layers using a backprojection algorithm. As an alternative to the EM algorithm, this thesis also introduces a method based on higher order tensors.
A result with potential applicatications in a number of diffeerent research fields is the extension of canonical correlation to handle complex variables. Correlation is maximized using a novel method that can handle singular covariance matrices.
Lundgren, Pär. "Using Homographies for Vehicle Motion Estimation." Thesis, Linköpings universitet, Reglerteknik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-120000.
Full textEl-Hameid, Hossam Hassan Abd. "Motion parameter estimation for autonomous vehicles." Thesis, Cranfield University, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.265750.
Full textKrause, Edward A. "Motion estimation for frame-rate conversion." Thesis, Massachusetts Institute of Technology, 1987. http://hdl.handle.net/1721.1/58490.
Full textVideocartridge only available in MIT Institute Archives.
Bibliography: leaves 177-180.
by Edward A. Krause.
Ph.D.
Hedborg, Johan. "Motion and Structure Estimation From Video." Doctoral thesis, Linköpings universitet, Datorseende, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-76904.
Full textVirtual Photo Set (VPS)
Peacock, Andrew M. "Information fusion for improved motion estimation." Thesis, University of Edinburgh, 2001. http://hdl.handle.net/1842/428.
Full textCook, Daniel A. "Synthetic Aperture Sonar Motion Estimation and Compensation." Thesis, Georgia Institute of Technology, 2007. http://hdl.handle.net/1853/14538.
Full textSari, Huseyin. "Motion Estimation Using Complex Discrete Wavelet Transform." Master's thesis, METU, 2003. http://etd.lib.metu.edu.tr/upload/1223205/index.pdf.
Full textBretzner, Lars. "Multi-scale feature tracking and motion estimation." Doctoral thesis, KTH, Numerisk analys och datalogi, NADA, 1999. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-2856.
Full textQC 20100519
Farnebäck, Gunnar. "Polynomial expansion for orientation and motion estimation." Doctoral thesis, Linköpings universitet, Bildbehandling, 2002. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-54282.
Full textKim, Jae-Hak, and Jae-Hak Kim@anu edu au. "Camera Motion Estimation for Multi-Camera Systems." The Australian National University. Research School of Information Sciences and Engineering, 2008. http://thesis.anu.edu.au./public/adt-ANU20081211.011120.
Full textHemmendorff, Magnus. "Motion estimation and compensation in medical imaging /." Linköping : Univ, 2001. http://www.bibl.liu.se/liupubl/disp/disp2001/tek703s.pdf.
Full textAndersson, Kenneth. "Motion estimation for perceptual image sequence coding /." Linköping : Univ, 2003. http://www.bibl.liu.se/liupubl/disp/disp2003/tek794s.pdf.
Full textMitikiri, Praveen Kumar. "Rate distortion analysis for conditional motion estimation." Thesis, Wichita State University, 2008. http://hdl.handle.net/10057/2010.
Full textThesis (M.S.)--Wichita State University, College of Engineering, Dept. of Electrical and Computer Engineering
Includes bibliographic references (leaves 28-31)
Armitano, Robert M. "Efficient motion-estimation algorithms for video coding." Diss., Georgia Institute of Technology, 1996. http://hdl.handle.net/1853/15397.
Full textChung, Hing-yip Ronald, and 鍾興業. "Fast motion estimation with search center prediction." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1999. http://hub.hku.hk/bib/B31220721.
Full textIldiz, Faith. "Estimation of motion parameters from image sequences." Thesis, Monterey, California. Naval Postgraduate School, 1991. http://hdl.handle.net/10945/28176.
Full textGuo, Yizhou. "Motion estimation and object-based video coding." Thesis, University of Bath, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.412348.
Full textYan, Hongshi. "Robust optical flow estimation and motion segmentation." Thesis, University of Warwick, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.422137.
Full textPorter, Sarah Victoria. "Video segmentation and indexing using motion estimation." Thesis, University of Bristol, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.402372.
Full textGONZALES, JOSE ANTONIO CASTINEIRA. "EVALUATING MOTION ESTIMATION ALGORITHMS FOR VIDEO COMPRESSION." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 1996. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=8711@1.
Full textThis work was performed to study motion estimation algorithms based on block matching in order to evaluate the importance of the choice of the motion estimation algorithm in the Project of a image sequence compression coder. In order to do so, they were studied four motion estimation algorithms, and their performance were evaluated considering some parameters such as search region size, methods to measure the matching between blocks and block sizes, related to the quality of the reconstructed image.
Liu, Peng. "Joint Estimation and Calibration for Motion Sensor." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-286839.
Full textI denna rapport utvecklas och implementeras en kalibreringsmethod för att skatta positionen för en grupp av accelerometrar placerade i en så kallad IMU sensor array. För att beskriva rörelsen för hela sensorgruppen, härleds en dynamisk tillståndsmodell. Problemställningen är då att skatta parametrarna i tillståndsmodellen. Detta löses med hjälp av Maximum Likelihood-metoden (ML) där två stycken algoritmer implementeras och analyseras. En baseras på Expectation Maximization (EM) och i den andra optimeras kostnadsfunktionen direkt med gradientsökning. I EM-algoritmen uppstår ett illa konditionerat delproblem i M-steget, vilket försämrar algoritmens prestanda, speciellt när det initiala felet är litet. Den resulterande MSE-kurvan kommer att avvika i detta fall. Däremot fungerar EM-algoritmen väl när antalet datasampel är tillräckligt och det initiala felet är större. I gradientsökningsmetoden undviks konditioneringsproblemen med hjälp av en omformulering. Slutligen analyseras medelkvadratfelet (MSE) för parameterskattningarna med hjälp av Monte Carlo-simulering. De resulterande MSE-kurvorna visar att gradientsökningsmetoden är mer robust mot numeriska problem, speciellt när det initiala felet är litet. Simuleringarna visar även att gradientsökning är robust mot brus.
Ruhnau, Paul. "Variational fluid motion estimation with physical priors." [S.l. : s.n.], 2006. http://madoc.bib.uni-mannheim.de/madoc/volltexte/2007/1432/.
Full textMitikiri, Praveen Kumar Namuduri Kamiswara. "Rate distortion analysis for conditional motion estimation." A link to full text of this thesis in SOAR, 2008. http://hdl.handle.net/10057/2010.
Full textCopyright 2008 by Praveen Kumar Mitikiri. All Rights Reserved. Includes bibliographical references (leaves 28-31).
Chan, Wing Cheong. "Fast global motion estimation and color interpolation /." View Abstract or Full-Text, 2002. http://library.ust.hk/cgi/db/thesis.pl?ELEC%202002%20CHANW.
Full textIncludes bibliographical references (leaves 74-76). Also available in electronic version. Access restricted to campus users.
Jiang, Hai. "Quantitative deformable motion estimation for biophysical analysis /." free to MU campus, to others for purchase, 2004. http://wwwlib.umi.com/cr/mo/fullcit?p3144427.
Full text"Motion estimation and segmentation." Thesis, 2008. http://library.cuhk.edu.hk/record=b6074551.
Full textFurthermore, we modified our proposed segmentation algorithm to handle video sequences that are already encoded in the H.264 format. Since the video is compressed, no spatial information is available. Instead, quantized transform coefficients of the residual frame are used to approximate spatial information and improve segmentation result. The computation time of the segmentation process is merely about 16ms per frame for CIF frame size video, allowing the algorithm to be applied in real-time applications such as video surveillance and conferencing.
In the first part of our research, we proposed a block matching algorithm called Fast Walsh Search (FWS) for video motion estimation. FWS employs two new error measures defined in Walsh Hadamard domain, which are partial sum-of-absolute difference (PSAD) and sum-of-absolute difference of DC coefficients (SADDCC). The algorithm first rejects most mismatched candidates using PSAD which is a coarse measure requiring little computation. Because of the energy packing ability of Walsh Hadamard transform (WHT) and the utilization of fast WHT computation algorithm, mismatched candidates are identified and rejected efficiently. Then the proposed algorithm identifies the matched candidate from the remaining candidates using SADDCC which is a more accurate measure and can reuse computation performed for PSAD. Experimental results show that FWS can give good visual quality to most of video scene with a reasonable amount of computation.
In the second part of our research, we developed a real-time video object segmentation algorithm. The motion information is obtained by FWS-VBS to minimize the computation time while maintaining an adequate accuracy. The algorithm makes use of the motion information to identify background motion model and moving objects. In order to preserve spatial and temporal continuity of objects, Markov random field (MRF) is used to model the foreground field. The block-based foreground object mask is obtained by minimizing the energy function of the MRF. The resulting object mask is then post-processed to generate a smooth object mask. Experimental results show that the proposed algorithm can effectively extract moving objects from different kind of sequences, at a speed of less than 100ms per frame for CIF frame size video.
Motion estimation is an important part in many video processing applications, such as video compression, object segmentation, and scene analysis. In all video compression applications, motion information is used to reduce temporal redundancy between frames, thus significantly reduce the required bitrate for transmission and storage of compressed video. In addition, in object-based video coding, video object can be automatically identified by its motion against the background.
Mak, Chun Man.
"June 2008."
Adviser: Wai-Kuen Cham.
Source: Dissertation Abstracts International, Volume: 70-03, Section: B, page: 1849.
Thesis (Ph.D.)--Chinese University of Hong Kong, 2008.
Includes bibliographical references.
Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web.
Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web.
Abstracts in English and Chinese.
School code: 1307.
Chen, Pei-Yao, and 陳沛堯. "Human Motion Extrapolation via Motion Analysis and 2D-3D Motion Estimation." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/81683950888361420836.
Full text淡江大學
資訊工程學系碩士班
99
The 3D virtual reality is a very popular research area over the last decade. The 3D products are proposed in video game industries. But most of the 3D products or researches didn’t use the real images or videos to generate, so we proposed a method to adopt the real 2D images to render 3D-liked vision. Our goal is to show the object like Google Map, we can rotate the object we load and according to the angle to show the corresponding object. Generally, if we can use more than one camera, and shooting the object from the surrounding each viewpoint. Then, the convergence of motion of switching angle will be very easy. Because we can directly obtain the matching time. But such preparatory work is too expensive. The main idea is shooting a human at multi-angle, then we observe the regular pattern of human and analyze the motion of human. Finally, infer a rule for the relationship between the change of viewpoint.
Chuan-Yu, Cho. "Adaptive Motion Estimation Algorithm for Varied Motion Contents and VLSI Motion Estimation Architecture Design for H.264/AVC." 2006. http://www.cetd.com.tw/ec/thesisdetail.aspx?etdun=U0016-0109200613403225.
Full textCho, Chuan-Yu, and 卓傳育. "Adaptive Motion Estimation Algorithm for Varied Motion Contents and VLSI Motion Estimation Architecture Design for H.264/AVC." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/03014446886289901505.
Full text國立清華大學
資訊工程學系
94
Motion estimation (ME) plays an important role in H.264 not only because it has extremely computational complexity, but also it affects the following block coding modes as well as the final coded bit-stream size. Therefore, studying on advance ME algorithms is one of the most efficient ways to improve the coding efficiency of a video codec. In thesis, we exhibit two ME schemes with software- and hardware-based implementations, respectively. Based on the studying on fast block-matching algorithms (FBMAs) and a priority list, the software-based ME scheme is started with a study on FBMAs, and then their efficiencies are illustrated in terms of algorithm checking points. A priority list is introduced to help with classification of motion content types of real world sequences. After doing statistical analyses on the proposed priority list and FBMAs, we propose a motion-content adaptive FBMA, which can adaptively switching searching strategies among three different FBMAs to maximize the coding efficiency under the considerations of motion-content variations. The latest H.264/AVC video coding standard adopts the variable block size (VBS) block partitions and multiple reference frames (MRF), which make the motion-compensation stage become extreme complicated. To save intermediate memory and maximum the hardware utilization, we propose an embedded merging scheme with a pipeline-based MRF extension. With this embedded design, only one copy of intermediate memory is required and fully utilization is expected after fulfilling the pipeline stages.
Demirdjian, D., and T. Darrell. "Motion Estimation from Disparity Images." 2001. http://hdl.handle.net/1721.1/6079.
Full textZhong, Kun-Zhe, and 鍾昆哲. "Backward Motion Estimation For Interpolation." Thesis, 1998. http://ndltd.ncl.edu.tw/handle/62855169049956264029.
Full textYu, Chong-Shou, and 余宗修. "Adaptive Fast Motion-Estimation Algorithms." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/06188544678702312191.
Full text國立成功大學
電機工程學系碩博士班
96
Videos, music and various multimedia objects can be seen in modern digital life everywhere. Multimedia communication relies on data compression technology in order to reduce the bits of data transmission. Video data are needed to be compressed before storage or transmission. Video compression exploits temporal redundancy between video frames to achieve higher compression efficiency. In most video coding standards motion compensation is the key function that does this job, which needs the information of a motion vector that is derived by motion estimation. Due to the heavy computational cost of motion estimation many fast algorithms have been proposed in recent years. Among them, some algorithms use a regional search that tweaks the result of the motion vector gradually. Some use logarithm based fast search strategies. However, small search pattern based motion-estimation algorithms usually spend large amounts of computational time in order to estimate large motion vectors, while other mid-sized search pattern algorithms usually spend extra search steps to confirm near-zero motion vectors. Divide and conquer methods, on the other hand, are not optimized for the probability model of motion vectors. This truth makes these logarithm based algorithms wasting additional time in estimating static motions which can easily be found by small search pattern based algorithms easily. In this dissertation three adaptive fast motion-estimation algorithms are proposed. The first of them employs a search pattern which is derived from the data clustering of motion vectors. The statistics of motion vectors are used to generate this pattern which is a pair of complementary double-layered (inner layer and outer layer) initial search patterns. The inner-layer search is applied first and tests for small motion. The outer layer search which is based on a logarithm search serves as a guard line to catch large motion. The simulation results show that the necessary computations have been reduced to 9~12 block matching per macroblock, which is much lower than the 14~16 block matchings of the famous efficient three-step search. The visual quality of the motion compensation result at that time is also better than most other algorithms. The second algorithm - adaptive double-layered initial search pattern (ADLISP) is an improved version of the first one. Motion prediction is employed by ADLISP to improve the search speed. The positions of the search points of ADLISP are also adaptive to recent motions. By using the pseudo median points of motion vector distribution probability, the simulation results of ADLISP show even better search efficiency over the logarithm-based fast motion-estimation algorithms. The average search points used per macroblock is decreased to 6.96, which is only half of the necessary amount of search points that efficient three-step search uses. On average, ADLISP only increases in the mean square error (MSE) of motion compensated video by 11.2%, which is nearly the same level compared to diamond search which is efficient in estimating small motions. The peak signal-to-noise (PSNR) loss is only 0.408dB compared to full search. In the third fast motion-estimation algorithm, the motion and distortion information of neighboring macroblocks are referenced to decide the best search mode. In different modes, different amounts of search points are used. The positions of these search points are adaptive to recent estimated motion vectors. Furthermore, an early search termination mechanism is used in some situations to save computation power. This algorithm tries to keep a suitable amount search points in suitable position to catch any scale of motions. Experimental results show that this algorithm can estimate motion vectors extremely quickly without conspicuous visual quality loss. Simulations in 23 different standard video test sequences show that the average necessary search points is reduced to 4.573, while the peak signal-to-noise loss is merely 0.336dB compared to full search.
SHI, SHYH-YUE, and 施世聿. "Motion Estimation Using Wavelet Trasnform." Thesis, 1994. http://ndltd.ncl.edu.tw/handle/10714463771594927502.
Full text國立中山大學
應用數學研究所
82
In this report, the moving tracks of objects in motion are derived by applying the Wavelet transforms. Conventionally, two major categories of motion estimation methods are used to find out the motion vector. The first one is the block matching method , which divides an image into blocks of the same size and compares the blocks in the current frame to the corresponding blocks in the previous frame to derive the best matching block. The motion vector can be obtained by estimating the corresponding block displacement. This method has the disadvantage that the result is sensitive to the choice of block size. The second category transforms the image by using certain transformation method, mostly, Fourier transform. But the Fourier transform method has the disadvantage that two objects with the same velocity can not be discriminated. Therefore, if there are two objects with the same velocity, they will be falsely identified as only one. Before applying Wavelet transform, the 2-dimensional moving function is first projected to both x-axis and y-axis. These two projections are then applied by Wavelet transform one at a time. By observing the transformed graph, the motion vector can be estimated. The initial position can be obtained. Two objects with the same velocity can also be discriminated. n-degree polynomials are used to approximate the tracks which can be described by smooth functions. In this report, an overview of various motion estimation methods is given first. Then an introduction of the Wavelet theory is presented. Next comes the application of Wavelet theory on the estimation of motion vector . Finally, computer simulations are performed and performances compared with that of the Fourier transform methods.