Digital video stabilization through curve warping techniques

Bosco, A.; Bruna, Arcangelo; Battiato, Sebastiano; Bella, Giampaolo; Puglisi, Giovanni

doi:10.1109/tce.2008.4560078

Cited by 53 publications

(32 citation statements)

References 10 publications

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“…The work of [20,21] on video stabilization, for example, uses integral projections of the intensity image to infer a 2D translation. The vertical and horizontal projections between frames i and iÀ 1 are registered (through cross-correlation or another registration technique), thus producing vertical and horizontal displacement estimations.…”

Section: Motivation and Proposed Methodsmentioning

confidence: 99%

Fast and accurate global motion compensation

Deniz

Bueno

Bermejo

et al. 2011

Pattern Recognition

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Section: Motivation and Proposed Methodsmentioning

confidence: 99%

Fast and accurate global motion compensation

Deniz

Bueno

Bermejo

et al. 2011

Pattern Recognition

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“…Therefore, x can be expressed as (see (21) at the bottom of the next page) From (4), (5), (17), (18), and (21), we obtain these equations …”

Section: Experiments Analysismentioning

confidence: 99%

“…Therefore, considerable research has been conducted to develop state-of-the art methods, which can be sorted into two major categories: namely, direct methods [2][3][4][5][6][7][8][9][10][11] and feature-based methods [12][13][14][15][16][17][18][19][20][21][22][23]. The direct methods recover the motion parameters based on direct image information and global minimisation criteria under the condition of assumptions such as brightness constancy, whereas feature-based approaches recover motion parameters based on the correspondences of a set of reliable features, which is first selected.…”

Section: Introductionmentioning

confidence: 99%

Video stabilisation based on modelling of motion imaging

Wang

et al. 2016

IET Image Processing

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This study proposes a novel digital video stabilisation scheme based on modelling of motion imaging (MI). The modelling of MI eliminates the speed motion as a result of a moving car, which is ignored in other models such as rotation + translation model, and estimates movement parameters of the background in video sequences captured from cameras mounted on moving cars. The authors first analyse the MI to understand the principle of the effects of car motion on MI, and select the matching method according to the proposed model. Then, they employ symmetric points to remove the speed motion. Finally, unwanted motion vector is stimulated by employing adaptive step-length filter, and the boundary compensating approach is employed to suppress the image jitter effectively. Their major contribution is the elimination of the effect of carrier's speed in motion estimation. Other contributions include new robust block matching approach and adaptive-step selection for motion filtering. They conduct experiments on real videos and artificial data. Experiments on real videos show that the proposed model can remove the effect of car motion, whereas the experiments on artificial data are conducted for theoretical analysis.

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“…Such matching causes error in presence of moving object because of random change in projection curve. In the same category, Bosco et al [8] proposed curve warping (CW) method. This method uses classical dynamic time warping instead of point-wise matching.…”

Section: Introductionmentioning

confidence: 99%

A robust video stabilization using optimized dynamic time warping

Shukla

Jha

2013

2013 IEEE Second International Conference on Image Information Processing (ICIIP-2013)

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Video stabilization has become a demanding field with the emerging compact and handy imaging devices in the market. Videos recorded with these devices mostly suffer from some unwanted jittery motions induced due to shaky hands or environmental vibrations. This paper presents an efficient Dynamic Time Warping (DTW) approach for the translational jitter stabilization in the recorded videos. The approach utilizes the dynamic programming for the optimized performance. The use of dynamic programming based DTW gives a significant improvement in the processing speed and memory consumption over the classical DTW approach. The algorithm has been tested on different categories of video like moving platform, homogeneous regions and low quality blurred videos, which are generally considered as bottleneck problems for accurate motion estimation. The proposed approach provides better stabilization in relation to the existing intensity based methods and the computational efficiency is inherited from recursive property of dynamic programming. Comparative analysis of results is given in terms of difference frame analysis and overall performance evaluation is given using interframe transformation fidelity (ITF) factor and processing time.

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Digital video stabilization through curve warping techniques

Abstract: Abstract

Cited by 53 publications

References 10 publications

Fast and accurate global motion compensation

Fast and accurate global motion compensation

Video stabilisation based on modelling of motion imaging

A robust video stabilization using optimized dynamic time warping

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