Reliable tracking algorithm for multiple reference frame motion estimation

Lee, Tsz-Kwan; Chan, Yui-Lam; Fu, Chang-Hong; Siu, Wan Chi

doi:10.1117/1.3605574

Cited by 2 publications

(2 citation statements)

References 22 publications

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“…3 To solve these problems, numerous algorithms have been proposed. [4][5][6] The online learning algorithm is one of the useful algorithms that has been widely used to solve the problem of objects' changing appearance. As some information of the objects to be tracked is known in advance in various scenarios, it is possible to employ prior knowledge to design the tracker.…”

Section: Introductionmentioning

confidence: 99%

Real-time tracking of deformable objects based on combined matching-and-tracking

Yan

Wang

2016

J. Electron. Imaging

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, "Real-time tracking of deformable objects based on combined matching-and-tracking," J. Electron. Imaging 25(2), 023011 (2016) Abstract. Visual tracking is very challenging due to the existence of several sources of variations, such as partial occlusion, deformation, scale variation, rotation, and background clutter. A model-free tracking method based on fusing accelerated features using fast explicit diffusion in nonlinear scale spaces (AKAZE) and KLT features is presented. First, matching-keypoints are generated by finding corresponding keypoints from the consecutive frames and the object template, then tracking-keypoints are generated using the forward-backward flow tracking method, and at last, credible keypoints are obtained by AKAZE-KLT tracking (AKT) algorithm. To avoid the instability of a statistical method, the median method is adopted to compute the object's location, scale, and rotation in each frame. The experimental results show that the AKT algorithm has strong robustness and can achieve accurate tracking especially under conditions of partial occlusion, scale variation, rotation, and deformation. The tracking performance shows higher robustness and accuracy in a variety of datasets and the average frame rate reaches 78 fps, showing good performance in real time. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

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Section: Introductionmentioning

confidence: 99%

Real-time tracking of deformable objects based on combined matching-and-tracking

Yan

Wang

2016

J. Electron. Imaging

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“…In Ref. 17, the MVs with the same characteristics are first merged and then the two most relevant MVs are selected to generate the MVof the current block. To apply the MV composition algorithm, the MVs of different block types must be stored for further calculation.…”

Section: Introductionmentioning

confidence: 99%

Adaptive search range adjustment and multiframe selection algorithm for motion estimation in H.264/AVC

Liu

Wang

2013

J. Electron. Imaging

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Abstract. The H.264/AVC video standard adopts a fixed search range (SR) and fixed reference frame (RF) for motion estimation. These fixed settings result in a heavy computational load in the video encoder. We propose a dynamic SR and multiframe selection algorithm to improve the computational efficiency of motion estimation. By exploiting the relationship between the predicted motion vector and the SR size, we develop an adaptive SR adjustment algorithm. We also design a RF selection scheme based on the correlation between the different block sizes of the macroblock. Experimental results show that our algorithm can significantly reduce the computational complexity of motion estimation compared with the JM15.1 reference software, with a negligible decrease in peak signal-tonoise ratio and a slight increase in bit rate. Our algorithm also outperforms existing methods in terms of its low complexity and high coding quality. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

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Reliable tracking algorithm for multiple reference frame motion estimation

Cited by 2 publications

References 22 publications

Real-time tracking of deformable objects based on combined matching-and-tracking

Real-time tracking of deformable objects based on combined matching-and-tracking

Adaptive search range adjustment and multiframe selection algorithm for motion estimation in H.264/AVC

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