Results 271 to 280 of about 4,160,080 (316)
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Joint Learning of Motion Estimation and Segmentation for Cardiac MR Image Sequences
International Conference on Medical Image Computing and Computer-Assisted Intervention, 2018Cardiac motion estimation and segmentation play important roles in quantitatively assessing cardiac function and diagnosing cardiovascular diseases. In this paper, we propose a novel deep learning method for joint estimation of motion and segmentation ...
C. Qin +6 more
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Philips Journal of Research, 1998
A layered motion estimation algorithm is proposed that permits quasisimultaneous motion estimation/segmentation up to a fixed maximum number of layers. The estimation results in one motion parameter set per layer, and a segmentation map that assigns these sets to different parts of the image (motion layers).
R.J. Schutten, A. Pelagotti, G. De Haan
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A layered motion estimation algorithm is proposed that permits quasisimultaneous motion estimation/segmentation up to a fixed maximum number of layers. The estimation results in one motion parameter set per layer, and a segmentation map that assigns these sets to different parts of the image (motion layers).
R.J. Schutten, A. Pelagotti, G. De Haan
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Motion Guided 3D Pose Estimation from Videos
European Conference on Computer Vision, 2020We propose a new loss function, called motion loss, for the problem of monocular 3D Human pose estimation from 2D pose. In computing motion loss, a simple yet effective representation for keypoint motion, called pairwise motion encoding, is introduced ...
Jingbo Wang +3 more
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[1989] Proceedings. Workshop on Visual Motion, 2003
The problem of using feature correspondences to recover the structure and 3D motion of a moving object from its successive images is analyzed. They formulate the problem as a quadratic minimization problem with a nonlinear constraint. Then they derive the condition for the solution to be optimal under the assumption of Gaussian noise in the input, in ...
M.E. Spetsakis, J. Aloimonos
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The problem of using feature correspondences to recover the structure and 3D motion of a moving object from its successive images is analyzed. They formulate the problem as a quadratic minimization problem with a nonlinear constraint. Then they derive the condition for the solution to be optimal under the assumption of Gaussian noise in the input, in ...
M.E. Spetsakis, J. Aloimonos
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Motion estimation with integrated motion models
Proceedings of the 42nd annual Southeast regional conference, 2004Conventional motion estimation algorithms rely on motion vectors characterizing translations and thus have limitations in capturing transformations of objects in video scenes such as scaling, rotations and deformations. In this paper, we introduce integrated motion models based on the Lie derivatives to improve the motion estimation accuracy.
Mahesh Nalasani +2 more
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Circuits, systems, and signal processing, 2021
F. H. Shajin, P. Rajesh, M. Raja
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F. H. Shajin, P. Rajesh, M. Raja
semanticscholar +1 more source
2009
Motion estimation in H.264/AVC supports quarter-pixel precision and is usually carried out in two phases: integer motion estimation (IME) and fractional motion estimation (FME). We have talked about IME in Chap.3. After IME finds an integer motion vector (IMV) for each of the 41 subblocks, FME performs motion search around the refinement center pointed
Youn-Long Steve Lin +3 more
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Motion estimation in H.264/AVC supports quarter-pixel precision and is usually carried out in two phases: integer motion estimation (IME) and fractional motion estimation (FME). We have talked about IME in Chap.3. After IME finds an integer motion vector (IMV) for each of the 41 subblocks, FME performs motion search around the refinement center pointed
Youn-Long Steve Lin +3 more
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Motion estimation on interlaced video
SPIE Proceedings, 2005Motion compensated de-interlacing and motion estimation based on Yen's generalisation of the sampling theorem (GST) have been proposed by Delogne and Vandendorpe. Motion estimation methods using three-fields have been designed on a block-by-block basis, minimising the difference between two GST predictions.
Ciuhu, Calina, de Haan, Gerard
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Motion Estimation using Tangent Distance
2007 IEEE International Conference on Image Processing, 2007In this paper, we present a method based on tangent distance to estimate motion in image sequences. Tangent distance combines an intuitive understanding and effective modeling of differences between patterns. This tool was first introduced and successfully applied in character recognition.
Fabrizio, Jonathan, Dubuisson, Séverine
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