Computational Experiments with a Feature Based Stereo Algorithm

Authors:
W. Eric L. Grimson
Affiliations:
Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139.
Venue:
IEEE Transactions on Pattern Analysis and Machine Intelligence
Year:
1985

Citing 0
Cited 18

Fuzzy Cognitive Maps for stereovision matching

Pattern Recognition
Stereovision depth analysis by two-dimensional motion charge memories

Pattern Recognition Letters
Modelling the Stereovision-Correspondence-Analysis task by Lateral Inhibition in Accumulative Computation problem-solving method

Expert Systems with Applications: An International Journal
Sparse view stereo matching

Pattern Recognition Letters
Multi-scale 3D scene flow from binocular stereo sequences

Computer Vision and Image Understanding
Visual surface segmentation from stereo

Image and Vision Computing
Towards a real-time 3D shape reconstruction using a structured light system

Pattern Recognition
Efficient hundreds-baseline stereo by counting interest points for moving omni-directional multi-camera system

Journal of Visual Communication and Image Representation
Optic flow goes stereo: a variational method for estimating discontinuity-preserving dense disparity maps

PR'05 Proceedings of the 27th DAGM conference on Pattern Recognition
Generation of 3d urban model using cooperative hybrid stereo matching

PCM'04 Proceedings of the 5th Pacific Rim conference on Advances in Multimedia Information Processing - Volume Part I
Image registration using triangular mesh

PCM'04 Proceedings of the 5th Pacific Rim conference on Advances in Multimedia Information Processing - Volume Part I
Road change detection algorithms in remote sensing environment

ICIC'05 Proceedings of the 2005 international conference on Advances in Intelligent Computing - Volume Part II
Real-time stereo vision on a reconfigurable system

SAMOS'05 Proceedings of the 5th international conference on Embedded Computer Systems: architectures, Modeling, and Simulation
Stereovision disparity analysis by two-dimensional motion charge map inspired in neurobiology

BVAI'05 Proceedings of the First international conference on Brain, Vision, and Artificial Intelligence
Generation of 3d building model using 3d line detection scheme based on line fitting of elevation data

PCM'05 Proceedings of the 6th Pacific-Rim conference on Advances in Multimedia Information Processing - Volume Part I
Image-Based drift and height estimation for helicopter landings in brownout

ICIAR'10 Proceedings of the 7th international conference on Image Analysis and Recognition - Volume Part II
Stereoscopic neuro-vision for three-dimensional object recognition

Mathematical and Computer Modelling: An International Journal
Automatic expert system for 3D terrain reconstruction based on stereo vision and histogram matching

Expert Systems with Applications: An International Journal

Quantified Score

Hi-index	0.15

Visualization

Abstract

Computational models of the human stereo system can provide insight into general information processing constraints that apply to any stereo system, either artificial or biological. In 1977 Marr and Poggio proposed one such computational model, which was characterized as matching certain feature points in difference-of-Gaussian filtered images and using the information obtained by matching coarser resolution representations to restrict the search space for matching finer resolution representations. An implementation of the algorithm and its testing on a range of images was reported in 1980. Since then a number of psychophysical experiments have suggested possible refinements to the model and modifications to the algorithm. As well, recent computational experiments applying the algorithm to a variety of natural images, especially aerial photographs, have led to a number of modifications. In this paper, we present a version of the Marr-Poggio-Grimson algorithm that embodies these modifications, and we illustrate its performance on a series of natural images.