Research on Video Saliency Detection Via Contrast and Self-Adaptive Transfer

Wang Yongguang; Hao Aimin; Li Shuai

doi:doi:10.11648/j.sd.20170502.14

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Research on Video Saliency Detection Via Contrast and Self-Adaptive Transfer

Wang Yongguang, Hao Aimin, Li Shuai

Published in Science Discovery (Volume 5, Issue 2)

Received: 20 April 2017 Accepted: Published: 20 April 2017

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Abstract

Although a lot of studies in salient motion detection have achieved great success in recent years, many challenges still exist toward the video saliency detection over the non-stationary videos and videos with slowly-moving objects, which supposes to exhibit significant influence on its corresponding subsequent applications. Thus, it urgently needs a more robust, stable, and precise method to solve the above mentioned limitations. In fact, inspired from the basic visualization rule of the human vision system, the human’s attention can be easily attracted by two independent factors: the motion saliency clue and the color saliency clue. Hence, this paper develops a novel salient motion detection method by fusing the motion saliency with the color saliency, which refines the preliminary saliency map by self-adaptive transfer via the newly designed intra-frame correlation. Also, comprehensive experimental results of our method toward the state-of-the-art methods over 4 public available benchmarks demonstrate the superiority of our method both in its robustness and high detection precision.

Published in	Science Discovery (Volume 5, Issue 2)
DOI	10.11648/j.sd.20170502.14
Page(s)	100-107
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Saliency Detection, Contrast, Self-Adaptive, Saliency-Transfer

References

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APA Style

Wang Yongguang, Hao Aimin, Li Shuai. (2017). Research on Video Saliency Detection Via Contrast and Self-Adaptive Transfer. Science Discovery, 5(2), 100-107. https://doi.org/10.11648/j.sd.20170502.14

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ACS Style

Wang Yongguang; Hao Aimin; Li Shuai. Research on Video Saliency Detection Via Contrast and Self-Adaptive Transfer. Sci. Discov. 2017, 5(2), 100-107. doi: 10.11648/j.sd.20170502.14

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AMA Style

Wang Yongguang, Hao Aimin, Li Shuai. Research on Video Saliency Detection Via Contrast and Self-Adaptive Transfer. Sci Discov. 2017;5(2):100-107. doi: 10.11648/j.sd.20170502.14

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@article{10.11648/j.sd.20170502.14,
  author = {Wang Yongguang and Hao Aimin and Li Shuai},
  title = {Research on Video Saliency Detection Via Contrast and Self-Adaptive Transfer},
  journal = {Science Discovery},
  volume = {5},
  number = {2},
  pages = {100-107},
  doi = {10.11648/j.sd.20170502.14},
  url = {https://doi.org/10.11648/j.sd.20170502.14},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sd.20170502.14},
  abstract = {Although a lot of studies in salient motion detection have achieved great success in recent years, many challenges still exist toward the video saliency detection over the non-stationary videos and videos with slowly-moving objects, which supposes to exhibit significant influence on its corresponding subsequent applications. Thus, it urgently needs a more robust, stable, and precise method to solve the above mentioned limitations. In fact, inspired from the basic visualization rule of the human vision system, the human’s attention can be easily attracted by two independent factors: the motion saliency clue and the color saliency clue. Hence, this paper develops a novel salient motion detection method by fusing the motion saliency with the color saliency, which refines the preliminary saliency map by self-adaptive transfer via the newly designed intra-frame correlation. Also, comprehensive experimental results of our method toward the state-of-the-art methods over 4 public available benchmarks demonstrate the superiority of our method both in its robustness and high detection precision.},
 year = {2017}
}

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TY  - JOUR
T1  - Research on Video Saliency Detection Via Contrast and Self-Adaptive Transfer
AU  - Wang Yongguang
AU  - Hao Aimin
AU  - Li Shuai
Y1  - 2017/04/20
PY  - 2017
N1  - https://doi.org/10.11648/j.sd.20170502.14
DO  - 10.11648/j.sd.20170502.14
T2  - Science Discovery
JF  - Science Discovery
JO  - Science Discovery
SP  - 100
EP  - 107
PB  - Science Publishing Group
SN  - 2331-0650
UR  - https://doi.org/10.11648/j.sd.20170502.14
AB  - Although a lot of studies in salient motion detection have achieved great success in recent years, many challenges still exist toward the video saliency detection over the non-stationary videos and videos with slowly-moving objects, which supposes to exhibit significant influence on its corresponding subsequent applications. Thus, it urgently needs a more robust, stable, and precise method to solve the above mentioned limitations. In fact, inspired from the basic visualization rule of the human vision system, the human’s attention can be easily attracted by two independent factors: the motion saliency clue and the color saliency clue. Hence, this paper develops a novel salient motion detection method by fusing the motion saliency with the color saliency, which refines the preliminary saliency map by self-adaptive transfer via the newly designed intra-frame correlation. Also, comprehensive experimental results of our method toward the state-of-the-art methods over 4 public available benchmarks demonstrate the superiority of our method both in its robustness and high detection precision.
VL  - 5
IS  - 2
ER  -

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Author Information

Wang Yongguang

State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Beijing, China
Hao Aimin

State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Beijing, China
Li Shuai

State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Beijing, China

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APA Style

Wang Yongguang, Hao Aimin, Li Shuai. (2017). Research on Video Saliency Detection Via Contrast and Self-Adaptive Transfer. Science Discovery, 5(2), 100-107. https://doi.org/10.11648/j.sd.20170502.14

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ACS Style

Wang Yongguang; Hao Aimin; Li Shuai. Research on Video Saliency Detection Via Contrast and Self-Adaptive Transfer. Sci. Discov. 2017, 5(2), 100-107. doi: 10.11648/j.sd.20170502.14

Copy | Download

AMA Style

Wang Yongguang, Hao Aimin, Li Shuai. Research on Video Saliency Detection Via Contrast and Self-Adaptive Transfer. Sci Discov. 2017;5(2):100-107. doi: 10.11648/j.sd.20170502.14

Copy | Download

@article{10.11648/j.sd.20170502.14,
  author = {Wang Yongguang and Hao Aimin and Li Shuai},
  title = {Research on Video Saliency Detection Via Contrast and Self-Adaptive Transfer},
  journal = {Science Discovery},
  volume = {5},
  number = {2},
  pages = {100-107},
  doi = {10.11648/j.sd.20170502.14},
  url = {https://doi.org/10.11648/j.sd.20170502.14},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sd.20170502.14},
  abstract = {Although a lot of studies in salient motion detection have achieved great success in recent years, many challenges still exist toward the video saliency detection over the non-stationary videos and videos with slowly-moving objects, which supposes to exhibit significant influence on its corresponding subsequent applications. Thus, it urgently needs a more robust, stable, and precise method to solve the above mentioned limitations. In fact, inspired from the basic visualization rule of the human vision system, the human’s attention can be easily attracted by two independent factors: the motion saliency clue and the color saliency clue. Hence, this paper develops a novel salient motion detection method by fusing the motion saliency with the color saliency, which refines the preliminary saliency map by self-adaptive transfer via the newly designed intra-frame correlation. Also, comprehensive experimental results of our method toward the state-of-the-art methods over 4 public available benchmarks demonstrate the superiority of our method both in its robustness and high detection precision.},
 year = {2017}
}

Copy | Download

TY  - JOUR
T1  - Research on Video Saliency Detection Via Contrast and Self-Adaptive Transfer
AU  - Wang Yongguang
AU  - Hao Aimin
AU  - Li Shuai
Y1  - 2017/04/20
PY  - 2017
N1  - https://doi.org/10.11648/j.sd.20170502.14
DO  - 10.11648/j.sd.20170502.14
T2  - Science Discovery
JF  - Science Discovery
JO  - Science Discovery
SP  - 100
EP  - 107
PB  - Science Publishing Group
SN  - 2331-0650
UR  - https://doi.org/10.11648/j.sd.20170502.14
AB  - Although a lot of studies in salient motion detection have achieved great success in recent years, many challenges still exist toward the video saliency detection over the non-stationary videos and videos with slowly-moving objects, which supposes to exhibit significant influence on its corresponding subsequent applications. Thus, it urgently needs a more robust, stable, and precise method to solve the above mentioned limitations. In fact, inspired from the basic visualization rule of the human vision system, the human’s attention can be easily attracted by two independent factors: the motion saliency clue and the color saliency clue. Hence, this paper develops a novel salient motion detection method by fusing the motion saliency with the color saliency, which refines the preliminary saliency map by self-adaptive transfer via the newly designed intra-frame correlation. Also, comprehensive experimental results of our method toward the state-of-the-art methods over 4 public available benchmarks demonstrate the superiority of our method both in its robustness and high detection precision.
VL  - 5
IS  - 2
ER  -

Copy | Download