Selectively de-animating video

Abstract

We present a semi-automated technique for selectively deanimating video to remove the large-scale motions of one or more objects so that other motions are easier to see. The user draws strokes to indicate the regions of the video that should be immobilized, and our algorithm warps the video to remove the large-scale motion of these regions while leaving finer-scale, relative motions intact. However, such warps may introduce unnatural motions in previously motionless areas, such as background regions. We therefore use a graph-cut-based optimization to composite the warped video regions with still frames from the input video; we also optionally loop the output in a seamless manner. Our technique enables a number of applications such as clearer motion visualization, simpler creation of artistic cinemagraphs (photos that include looping motions in some regions), and new ways to edit appearance and complicated motion paths in video by manipulating a de-animated representation. We demonstrate the success of our technique with a number of motion visualizations, cinemagraphs and video editing examples created from a variety of short input videos, as well as visual and numerical comparison to previous techniques.

Document Details

Document Type
Pub Defense Publication
Publication Date
Jul 01, 2012
Source ID
10.1145/2185520.2185562

Entities

People

  • Aseem Agarwala
  • Jiamin Bai
  • Maneesh Agrawala
  • Ravi Ramamoorthi

Organizations

  • Adobe
  • Division of Computing and Communication Foundations
  • Division of Information and Intelligent Systems
  • Office of Naval Research
  • University of California, Berkeley

Tags

Fields of Study

  • Computer science

Readers

  • Control Systems Engineering.
  • Database Systems and Applications
  • Human-Computer Interaction (HCI).