Visibility maps for improving seam carving

  • Authors:
  • Alex Mansfield;Peter Gehler;Luc Van Gool;Carsten Rother

  • Affiliations:
  • Computer Vision Laboratory, ETH Zürich, Switzerland;Computer Vision Laboratory, ETH Zürich, Switzerland;Computer Vision Laboratory, ETH Zürich, Switzerland, ESAT-PSI, KU Leuven, Belgium;Microsoft Research Ltd, Cambridge, UK

  • Venue:
  • ECCV'10 Proceedings of the 11th European conference on Trends and Topics in Computer Vision - Volume Part II
  • Year:
  • 2010

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Abstract

In this paper, we present a new, improved seam carving algorithm. Seam carving efficiently removes pixels from an image to produce a retargeted image. It has proved popular with users and has been used as a component in many retargeting algorithms. We introduce the visibility map, a new framework for pixel removing image editing methods. This allows us to cast retargeting as a binary graph labelling problem. We derive a general algorithm which uses seam carving operations for efficient greedy optimization of a well defined energy, and compare this with forward energy seam carving and shift map image editing. We test this method with varying parameters on a large number of images, and present an improved seam carving algorithm which can demonstrably produce better results. We draw general conclusions about pixel removing methods for retargeting and motivate future directions of research.