Distancecut: Interactive Real-Time Segmentation and Matting of Images and Videos (PREPRINT)

Abstract

An interactive algorithm for soft segmentation and matting of natural images and videos is presented in this paper. The technique follows and extends [11], where the user first roughly scribbles/labels different regions of interest, and from them the whole data is automatically segmented. The segmentation and alpha matte are obtained from the fast, linear complexity, computation of weighted distances to the user-provided scribbles. These weighted distances assign probabilities to each labelled class for every pixel. The weights are derived from models of the image regions obtained from the user provided scribbles via kernel density estimation. The matting results follow from combining this density and the computed weighted distances. We present the underlying framework and examples showing the capability of the algorithm to segment and compute alpha mattes in interactive real time, for difficult natural data.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2007
Accession Number
ADA478613

Entities

People

  • Guillermo Sapiro
  • Xue Bai

Organizations

  • University of Minnesota

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Boundaries
  • Computations
  • Computer Vision
  • Image Segmentation
  • Information Operations
  • Mathematical Analysis
  • Mathematics
  • Minnesota
  • Probability
  • Universities

Fields of Study

  • Computer science

Readers

  • Computer Vision.
  • Regression Analysis.