A robust digital image stabilization technique based on inverse triangle method and background detection

Hsu, S. Y.; Liang, Sheng-Fu; Lin, Chin‐Teng

doi:10.1109/tce.2005.1467968

Cited by 51 publications

(3 citation statements)

References 22 publications

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“…It has been widely used in the areas of video surveillance, panorama stitching, robot localization and moving objects tracking [4][5][6][7]. However, making a stable video is a very challenging task especially when an motion of both camera (ego-motion and high-frequency motion) and foreground objects is present,The stabilization accuracy profoundly affects the stabilization quality and impedes the subsequent processes for various applications [8,9].…”

Section: Introductionmentioning

confidence: 99%

Improved Image Alignment Algorithm Based on Projective Invariant for Aerial Video Stabilization

2014

KSII TIIS

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In many moving object detection problems of an aerial video, accurate and robust stabilization is of critical importance. In this paper, a novel accurate image alignment algorithm for aerial electronic image stabilization (EIS) is described. The feature points are first selected using optimal derivative filters based Harris detector, which can improve differentiation accuracy and obtain the precise coordinates of feature points. Then we choose the Delaunay Triangulation edges to find the matching pairs between feature points in overlapping images. The most "useful" matching points that belong to the background are used to find the global transformation parameters using the projective invariant. Finally, intentional motion of the camera is accumulated for correction by Sage-Husa adaptive filtering. Experiment results illustrate that the proposed algorithm is applied to the aerial captured video sequences with various dynamic scenes for performance demonstrations.

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Section: Introductionmentioning

confidence: 99%

Improved Image Alignment Algorithm Based on Projective Invariant for Aerial Video Stabilization

2014

KSII TIIS

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“…Unlike in other applications, motion estimation in video stabilization has to put up with great replacement in consecutive frames for the movement between frames is very intense. In order to cope with the problem, various methods have been proposed [1][2][3][4][5], such as optical flow equation [1,2] block-matching method [3], gray projection algorithm [4] and 2D FFT [5]. However, these methods may lose their validity in some cases.…”

Section: Introductionmentioning

confidence: 99%

“…Provide that we already know the rotated angle T between two matched feature points ( can be computed by(4).…”

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confidence: 99%

Edge Mapping: A New Motion Estimation Method for Video Stabilization

Liu

Zhang

Xie

et al. 2008

2008 International Symposium on Computer Science and Computational Technology

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Video stabilization is a technology to remove the dithering between frames in a video sequence by motion estimation, motion filter and motion compensation. In this paper, we focus on the motion estimation (ME) step which is known as the most important part for a successful video stabilization system because the latter processing heavily relies on it. However, traditional ME methods mainly hypothesize that the movement within frames only consists of displacement. So their methods will lose their validity on the occasion when rotation is also presented. To solve this problem, interest points matching (IPM) was often suggested as suitable solution. But to determine the parameter of interest point and to get a reliable match result involve a lot of computation load. Hence, we proposed a novel motion estimation scheme which uses edge points as interest points and then follows a coarse-to-fine matching method to obtain the motion parameter. Experiment shows our method can achieve a robust performance under various environments and the processing time is less than traditional corners based IPM methods.

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Binary Edge Based Adaptive Motion Correction for Accurate and Robust Digital Image Stabilization

Kwon

Nam

Paik

2006

Advances in Image and Video Technology

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A robust digital image stabilization technique based on inverse triangle method and background detection

Cited by 51 publications

References 22 publications

Improved Image Alignment Algorithm Based on Projective Invariant for Aerial Video Stabilization

Improved Image Alignment Algorithm Based on Projective Invariant for Aerial Video Stabilization

Edge Mapping: A New Motion Estimation Method for Video Stabilization

Binary Edge Based Adaptive Motion Correction for Accurate and Robust Digital Image Stabilization

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