Multi-scale 3D Scene Flow from Binocular Stereo Sequences (Preprint)

Abstract

Scene flow methods estimate the three-dimensional motion field for points in the world using multi-camera video data. Such methods combine multi-view reconstruction with motion estimation. This paper describes an alternative formulation for dense scene flow estimation that provides reliable results using only two cameras by fusing stereo and optical flow estimation into a single coherent framework. Internally, the proposed algorithm generates probability distributions for optical flow and disparity. Taking into account the uncertainty in the intermediate stages allows for more reliable estimation of the 3D scene flow than previous methods allow. To handle the aperture problems inherent in the estimation of optical flow and disparity, a multi-scale method along with a novel region-based technique is used within a regularized solution. This combined approach both preserves discontinuities and prevents over-regularization - to problems commonly associated with the basic multi-scale approaches. Experiments with synthetic and real test data demonstrate the strength of the proposed approach.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2007
Accession Number
ADA470442

Entities

People

  • Rui Li
  • Stan Sclaroff

Organizations

  • Boston University

Tags

Communities of Interest

  • Air Platforms
  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Accuracy
  • Algorithms
  • Binoculars
  • Computational Science
  • Computations
  • Computer Science
  • Computer Vision
  • Data Sets
  • Discontinuities
  • Disparities
  • Flow Fields
  • Gaussian Noise
  • Image Segmentation
  • Kalman Filters
  • Optimal Estimators
  • Random Variables
  • Sequences

Fields of Study

  • Computer science

Readers

  • Computational Fluid Dynamics (CFD)
  • Computer Vision.