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Segmentation and motion estimation
1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings, 2002We present an algorithm that combines image segmentation and motion field estimation. The segmentation includes the occluded and uncovered background regions, the self-occluded and uncovered object regions, and the common moving regions of the objects.
Hamid Naseri, John A. Stuller
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Motion estimation and segmentation
Machine Vision and Applications, 1996In the general structure-from-motion (SFM) problem involving several moving objects in a scene, the essential first step is to segment moving objects independently. We attempt to deal with the problem of optical flow estimation and motion segmentation over a pair of images. We apply a mean field technique to determine optical flow and motion boundaries
Tina Yu Tian, Mubarak Shah
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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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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 ...
Chen Qin +6 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.
Calina Ciuhu, Gerard 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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Optimal motion and structure estimation
Proceedings CVPR '89: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 1993The problem of estimating motion and structure of a rigid scene from two perspective monocular views is studied. The optimization approach presented is motivated by the following observations of linear algorithms: (1) for certain types of motion, even pixel-level perturbations (such as digitization noise) may override the information characterized by ...
Juyang Weng +2 more
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A Fast Motion Estimation Using Prediction of Motion Estimation Error
2004This paper presents a modified MSEA (multi-level successive elimination algorithm) which gives less computational complexity. We predict a motion estimation error using the norms at the already processed levels in the MSEA scheme and then decide on if the following levels should be proceeded using the predicted result.
Hyun Soo Kang 0001 +4 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
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3D ego-Motion Estimation Using low-Cost mmWave Radars via Radar Velocity Factor for Pose-Graph SLAM
IEEE Robotics and Automation Letters, 2021Yeong-Sang Park +3 more
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