Optimum polygonal approximation of digitized curves
Pattern Recognition Letters
Video summarization by curve simplification
MULTIMEDIA '98 Proceedings of the sixth ACM international conference on Multimedia
Proceedings of the 27th annual conference on Computer graphics and interactive techniques
SIGGRAPH '84 Proceedings of the 11th annual conference on Computer graphics and interactive techniques
AVE: automated home video editing
MULTIMEDIA '03 Proceedings of the eleventh ACM international conference on Multimedia
Interactive digital photomontage
ACM SIGGRAPH 2004 Papers
Video enhancement using per-pixel virtual exposures
ACM SIGGRAPH 2005 Papers
Making a Long Video Short: Dynamic Video Synopsis
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Computational video enhancement
Computational video enhancement
COMPSAC '09 Proceedings of the 2009 33rd Annual IEEE International Computer Software and Applications Conference - Volume 02
ACM SIGGRAPH 2010 papers
ACM SIGGRAPH 2010 papers
Technical Section: Real-time temporal shaping of high-speed video streams
Computers and Graphics
Selectively de-animating video
ACM Transactions on Graphics (TOG) - SIGGRAPH 2012 Conference Proceedings
Automated video looping with progressive dynamism
ACM Transactions on Graphics (TOG) - SIGGRAPH 2013 Conference Proceedings
CameraMatch: automatic recognition of subjects using smartphones-toward entertaining photo sessions
CHI '13 Extended Abstracts on Human Factors in Computing Systems
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We present methods for generating novel time-lapse videos that address the inherent sampling issues that arise with traditional photographic techniques. Starting with video-rate footage as input, our post-process downsamples the source material into a time-lapse video and provides user controls for retaining, removing, and resampling events. We employ two techniques for selecting and combining source frames to form the output. First, we present a non-uniform sampling method, based on dynamic programming, which optimizes the sampling of the input video to match the user's desired duration and visual objectives. We present multiple error metrics for this optimization, each resulting in different sampling characteristics. To complement the non-uniform sampling, we present the virtual shutter, a non-linear filtering technique that synthetically extends the exposure time of time-lapse frames.