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2010 IEEE International Conference on Image Processing, 2010
Motion estimation is known to be a non-convex optimization problem. This non-convexity comes from several ambiguities in motion estimation such as the aperture problem, or fast motion relative to the magnitude of the image gradient. In this paper, we propose a fast random search algorithm to estimate motion.
Sylvain Boltz, Frank Nielsen
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Motion estimation is known to be a non-convex optimization problem. This non-convexity comes from several ambiguities in motion estimation such as the aperture problem, or fast motion relative to the magnitude of the image gradient. In this paper, we propose a fast random search algorithm to estimate motion.
Sylvain Boltz, Frank Nielsen
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Motion estimation optimization
[Proceedings] ICASSP-92: 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing, 1992Motion estimation is cast as a problem in energy minimization. This is achieved by modeling the displacement field as a Markov random field. The equivalence of a Markov random field and a Gibbs distribution is then used to convert the problem into one of defining an appropriate energy function that describes the motion and any constraints imposed on it.
Sarah A. Rajala +3 more
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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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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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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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Motion Vector Smoothing for True Motion Estimation
2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings, 2006This paper proposes a new motion vector (MV) smoothing algorithm to track the real motion in image sequences for MPEG video encoders. First, a pre-checking algorithm is employed to eliminate wrong motion vectors and preserve all possible motion vectors.
Hai Bing Yin +4 more
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Head motion classification with 2D motion estimation
2014 22nd Signal Processing and Communications Applications Conference (SIU), 2014This work aims to classify the changes in head pose of a user sitting in front of a screen by using the estimated head rotation. Considered classes include ∓15, ∓30, ve ∓ 45 degree pan, tilt and combinations of these poses. SIFT flow algorithm is used for motion estimation.
Inci M. Baytas, Bilge Günsel
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