Best Computer Vision Paper Award by Google Research for 2011

Our following paper was just awarded the Excellent Paper for 2011 in Computer Vision by Google Research.

  • M. Grundmann, V. Kwatra, and I. Essa (2011), “Auto-Directed Video Stabilization with Robust L1 Optimal Camera Paths,” in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2011. [PDF] [WEBSITE] [VIDEO] [DEMO] [DOI] [BIBTEX]
    @InProceedings{ 2011-Grundmann-AVSWROCP,
    author  = {M. Grundmann and V. Kwatra and I. Essa},
    booktitle  = {{IEEE Conference on Computer Vision and Pattern
    Recognition (CVPR)}},
    demo = {},
    doi = {10.1109/CVPR.2011.5995525},
    month = {June},
    pdf = {},
    publisher  = {IEEE Computer Society},
    title = {Auto-Directed Video Stabilization with Robust L1
    Optimal Camera Paths},
    url = {},
    video = {},
    year = {2011}

Casually shot videos captured by handheld or mobile cameras suffer from significant amount of shake. Existing in-camera stabilization methods dampen high-frequency jitter but do not suppress low-frequency movements and bounces, such as those observed in videos captured by a walking person. On the other hand, most professionally shot videos usually consist of carefully designed camera configurations, using specialized equipment such as tripods or camera dollies, and employ ease-in and ease-out for transitions. Our stabilization technique automatically converts casual shaky footage into more pleasant and professional looking videos by mimicking these cinematographic principles. The original, shaky camera path is divided into a set of segments, each approximated by either constant, linear or parabolic motion, using an algorithm based on robust L1 optimization. The stabilizer has been part of the YouTube Editor since March 2011.
via Research Blog.

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