Results 211 to 220 of about 140,266 (262)
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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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Motion estimation in hazy videos
Pattern Recognition Letters, 2021Abstract Motion estimation is the basic need for the success of many video analysis algorithms such as moving object detection, human activity recognition, etc. Most of the motion estimation algorithms are prone to weather conditions and thus, they fail to estimate the motion in degraded weather. Severe weather situations like snow, rain, haze, smog,
Sachin Chaudhary +4 more
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Estimate Large Motions Using the Reliability-Based Motion Estimation Algorithm
International Journal of Computer Vision, 2006Detecting and estimating motions of fast moving objects has many important applications. However, most existing motion estimation techniques have difficulties in handling large motions in the scene. In this paper, we extend our recently proposed reliability-based stereo vision technique to solving large motion estimation problem.
Minglun Gong, Yee-Hong Yang
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Predictive motion estimation with global motion predictor
SPIE Proceedings, 2004Predictive motion estimation techniques have become widely used in video coding systems due to their reasonable coding performance and low computational requirement compared to the brute force full search method. However, most existing predictive motion estimation algorithms focus mainly on local motions and consider motion predictions from only ...
Shijun Sun, Shawmin Lei
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Global motion estimation combining with motion segmentation
SPIE Proceedings, 2013In order to improve the accuracy of global motion estimation (GME), a new method for GME combining with motion segmentation is proposed in this paper. The proposed method removes motion vector (MV) outliers and implements initial motion segmentation by analyzing properties of motion vectors.
Yaxiang Zhao +2 more
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Advanced Motion Estimation and Motion Compensated De-Interlacing
International Workshop on HDTV '96, 1996This paper describes a new high quality de-interlacing algorithm applying motion estimation and compensation techniques. First, a comparison between two recently introduced de-interlacing concepts will be presented. One method is based on a generalized sampling theorem and the other uses time-recursion.
Bellers, E. B., de Haan, G.
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Motion sickness estimation system
The 2012 International Joint Conference on Neural Networks (IJCNN), 2012Motion sickness occurs when the brain receives conflicting sensory information from body, inner ear and eyes [1]. In some cases, a decreased ability to actively control the body's postural motion also causes motion sickness [2][3]. Many previous studies have indicated that motion sickness had negative effect on driving performance, and sometimes lead ...
Chin-Teng Lin +5 more
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