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Video segmentation and stabilization for BallCam

Published:16 March 2017Publication History

ABSTRACT

We present a video stabilization algorithm for ball camera systems that undergo extreme egomotion during sports play. In particular, we focus on the BallCam system which is an American football embedded with an action camera at the tip of the ball. We propose an activity-aware video stabilization algorithm which is able to understand the current activity of the BallCam, which uses estimated activity labels to inform a robust video stabilization algorithm. Activity recognition is performed with a deep convolutional neural network, which uses optical flow.

References

  1. Kitani, K., Horita, K., Koike, H.: Ballcam!: dynamic view synthesis from spinning cameras. In: Adjunct proceedings of the 25th annual ACM symposium on User interface software and technology, ACM (2012) Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Pfeil, J., Hildebrand, K., Gremzow, C., Bickel, B., Alexa, M.: Throwable panoramic ball camera. In: SIGGRAPH Asia 2011 Emerging Technologies, ACM (2011) Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Grundmann, M., Kwatra, V., Essa, I.: Auto-directed video stabilization with robust l1 optimal camera paths. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR). (2011) Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Farnebäck, G.: Two-frame motion estimation based on polynomial expansion. In: Image analysis. Springer (2003) 363--370 Google ScholarGoogle ScholarDigital LibraryDigital Library

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  • Published in

    cover image ACM Other conferences
    AH '17: Proceedings of the 8th Augmented Human International Conference
    March 2017
    264 pages
    ISBN:9781450348355
    DOI:10.1145/3041164

    Copyright © 2017 Copyright is held by the owner/author(s)

    Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    • Published: 16 March 2017

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    Qualifiers

    • demonstration

    Acceptance Rates

    Overall Acceptance Rate121of306submissions,40%

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