skip to main content
10.1145/3610543.3626171acmconferencesArticle/Chapter ViewAbstractPublication Pagessiggraph-asiaConference Proceedingsconference-collections
research-article

Footstep Detection for Film Sound Production

Authors Info & Claims
Published:28 November 2023Publication History

ABSTRACT

In this paper, we presented a footstep detection method, which could assist sound editors in positioning the character’s footsteps on the timeline of the film. Based on it, a footstep detection system was designed for film sound production. Considering the characteristics of human motion and the needs of film sound production, our method included two parts: data preprocessing and footstep detection modeling. Experiments on various types of shots showed the good generalization and high accuracy of our method. The application evaluation demonstrated the high efficiency of the system.

References

  1. Z. Cao, G. Hidalgo, T. Simon, S. Wei, and Y. Sheikh. 2021. OpenPose: Realtime Multi-Person 2D Pose Estimation Using Part Affinity Fields. IEEE Transactions on Pattern Analysis and Machine Intelligence 43, 01 (jan 2021), 172–186. https://doi.org/10.1109/TPAMI.2019.2929257Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. J. Carreira and Andrew Zisserman. 2017. Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset. 4724–4733. https://doi.org/10.1109/CVPR.2017.502Google ScholarGoogle ScholarCross RefCross Ref
  3. MMPose Contributors. 2020a. OpenMMLab Pose Estimation Toolbox and Benchmark. https://github.com/open-mmlab/mmpose.Google ScholarGoogle Scholar
  4. MMAction2 Contributors. 2020b. OpenMMLab’s Next Generation Video Understanding Toolbox and Benchmark. https://github.com/open-mmlab/mmaction2.Google ScholarGoogle Scholar
  5. Anastasios Dimou, Olivia Nemethova, and Markus Rupp. 2005. SCENE CHANGE DETECTION FOR H.264 USING DYNAMIC THRESHOLD TECHNIQUES. https://api.semanticscholar.org/CorpusID:16772266Google ScholarGoogle Scholar
  6. Hao-Shu Fang, Jiefeng Li, Hongyang Tang, Chao Xu, Haoyi Zhu, Yuliang Xiu, Yong-Lu Li, and Cewu Lu. 2022. AlphaPose: Whole-Body Regional Multi-Person Pose Estimation and Tracking in Real-Time. IEEE Transactions on Pattern Analysis and Machine Intelligence (2022).Google ScholarGoogle Scholar
  7. Hao-Shu Fang, Shuqin Xie, Yu-Wing Tai, and Cewu Lu. 2017. RMPE: Regional Multi-person Pose Estimation. In 2017 IEEE International Conference on Computer Vision (ICCV). 2353–2362. https://doi.org/10.1109/ICCV.2017.256Google ScholarGoogle ScholarCross RefCross Ref
  8. Francois Faure, Gilles Debunne, Marie-Paule Cani, and Franck Multon. 2001. Dynamic Analysis of Human Walking. 8th Eurographics Workshop on Computer Animation and Simulation (04 2001). https://doi.org/10.1007/978-3-7091-6874-5_4Google ScholarGoogle ScholarCross RefCross Ref
  9. Christoph Feichtenhofer, Haoqi Fan, Jitendra Malik, and Kaiming He. 2019. Slowfast networks for video recognition. In Proceedings of the IEEE international conference on computer vision. 6202–6211.Google ScholarGoogle ScholarCross RefCross Ref
  10. Kamiar Kordari, Benjamin Funk, Jared Napora, Ruchika Verma, Carole Teolis, and Travis Young. 2015. Method for step detection and gait direction estimation.Google ScholarGoogle Scholar
  11. Ji Lin, Chuang Gan, and Song Han. 2019. TSM: Temporal Shift Module for Efficient Video Understanding. In Proceedings of the IEEE International Conference on Computer Vision.Google ScholarGoogle ScholarCross RefCross Ref
  12. Dahua Lin Yue Zhao, Yuanjun Xiong. 2019. MMAction. https://github.com/open-mmlab/mmaction.Google ScholarGoogle Scholar
  13. Patryk Łaś and Piotr Wisniowski. 2021. Method of Step Detection and Counting Based on Measurements of Magnetic Field Variations. Sensors 21 (11 2021), 7775. https://doi.org/10.3390/s21237775Google ScholarGoogle ScholarCross RefCross Ref

Index Terms

  1. Footstep Detection for Film Sound Production

          Recommendations

          Comments

          Login options

          Check if you have access through your login credentials or your institution to get full access on this article.

          Sign in
          • Published in

            cover image ACM Conferences
            SA '23: SIGGRAPH Asia 2023 Technical Communications
            November 2023
            127 pages
            ISBN:9798400703140
            DOI:10.1145/3610543

            Copyright © 2023 ACM

            Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

            Publisher

            Association for Computing Machinery

            New York, NY, United States

            Publication History

            • Published: 28 November 2023

            Permissions

            Request permissions about this article.

            Request Permissions

            Check for updates

            Qualifiers

            • research-article
            • Research
            • Refereed limited

            Acceptance Rates

            Overall Acceptance Rate178of869submissions,20%
          • Article Metrics

            • Downloads (Last 12 months)81
            • Downloads (Last 6 weeks)11

            Other Metrics

          PDF Format

          View or Download as a PDF file.

          PDF

          eReader

          View online with eReader.

          eReader

          HTML Format

          View this article in HTML Format .

          View HTML Format