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An Approach of Short Advertising Video Generation Using Mobile Phone Assisted by Robotic Arm

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Advances in Computer Graphics (CGI 2020)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 12221))

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Abstract

Recently, Short Advertising Video has become an increasingly dominant form of advertisement on social media. However, making Short Advertising Video is a challenging task for micro and small businesses, since it requires professional skills and years of experience. In this paper, we present a novel approach of Short Advertising Video generation assisted by robotic arms. We analyzed the professional composition and imaging of advertising videos, and transformed them into an automatic shooting process during the production of Short Advertising Video, assisted by a robotic arm. Practically, we applied our approach in two kinds of robotic arms and the results showed that robotic arm assist solution can highly enhance the efficiency and effect of making Short Advertising Video. In addition, our video generation approach can save time and money for novice users from micro and small business who has very limit resources and budget. And, we believe that our approach might overturn the existing production model of the Short Advertising Video propagated in the online business and social media.

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Notes

  1. 1.

    https://gvmled.com.

  2. 2.

    https://www.dji.com/osmo.

  3. 3.

    http://motorizedprecision.com.

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Author information

Authors and Affiliations

  1. Informatics School, Xiamen University, Xiamen, China

    Jiefeng Li, Yingying She, Yalan Luo, Hao He & Weiyue Lin

  2. College of Art, Xiamen University, Xiamen, China

    Lin Lin & Shengjing Hou

  3. Quanzhou Institute of Equipment Manufacturing Haixi Institute, Chinese Academy of Science, Quanzhou, China

    Hao He

Authors
  1. Jiefeng Li
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  2. Yingying She
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  3. Lin Lin
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  4. Yalan Luo
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  5. Hao He
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  6. Weiyue Lin
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  7. Shengjing Hou
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Corresponding authors

Correspondence to Yingying She or Lin Lin .

Editor information

Editors and Affiliations

  1. University of Geneva, Geneva, Switzerland

    Nadia Magnenat-Thalmann

  2. University of Crete, Heraklion, Greece

    Constantine Stephanidis

  3. University of Macau, Macau, China

    Enhua Wu

  4. Swiss Federal Institute of Technology, Lausanne, Switzerland

    Daniel Thalmann

  5. Shanghai Jiao Tong University, Shanghai, China

    Bin Sheng

  6. University of Sydney, Sydney, Australia

    Jinman Kim

  7. University of Crete, Heraklion, Greece

    George Papagiannakis

  8. University of Calgary, Calgary, AB, Canada

    Marina Gavrilova

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Li, J. et al. (2020). An Approach of Short Advertising Video Generation Using Mobile Phone Assisted by Robotic Arm. In: Magnenat-Thalmann, N., et al. Advances in Computer Graphics. CGI 2020. Lecture Notes in Computer Science(), vol 12221. Springer, Cham. https://doi.org/10.1007/978-3-030-61864-3_14

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  • DOI: https://doi.org/10.1007/978-3-030-61864-3_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-61863-6

  • Online ISBN: 978-3-030-61864-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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