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On binocularly viewed occlusion junctions

https://doi.org/10.1007/bfb0015533
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/bf00128527openalex-snapshot
Interpreting line drawings of curved objects
inferredcites →https://doi.org/10.1007/bf00129682openalex-snapshot
Surface shape from the deformation of apparent contours
inferredcites →https://doi.org/10.1016/0004-3702(71)90005-1openalex-snapshot
On seeing things
inferredcites →https://doi.org/10.1016/0042-6989(67)90091-0openalex-snapshot
Stereopsis and anomalous contour
inferredcites →https://doi.org/10.1016/0042-6989(90)90161-dopenalex-snapshot
Da vinci stereopsis: Depth and subjective occluding contours from unpaired image points
inferredcites →https://doi.org/10.1016/0262-8856(92)90015-uopenalex-snapshot
Computational framework for determining stereo correspondence from a set of linear spatial filters
inferredcites →https://doi.org/10.1037//0033-295x.101.3.414openalex-snapshot
Toward a general theory of stereopsis: Binocular matching, occluding contours, and fusion.
inferredcites →https://doi.org/10.1037//0033-295x.102.4.705openalex-snapshot
A theoretical analysis of illusory contour formation in stereopsis.
inferredcites →https://doi.org/10.1038/367365a0openalex-snapshot
The role of partial occlusion in stereopsis
inferredcites →https://doi.org/10.1068/p170753openalex-snapshot
Planarity and Segmentation in Stereoscopic Matching
inferredcites →https://doi.org/10.1109/cvpr.1992.223143openalex-snapshot
A Bayesian treatment of the stereo correspondence problem using half-occluded regions

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1006/cviu.1997.0602openalex-snapshot
Image Analysis and Computer Vision: 1996
inferred← citeshttps://doi.org/10.1007/11744078_41openalex-snapshot
Rethinking the Prior Model for Stereo
inferred← citeshttps://doi.org/10.1007/3-540-48432-9_6openalex-snapshot
Bayesian Models for Finding and Grouping Junctions
inferred← citeshttps://doi.org/10.1007/bfb0055670openalex-snapshot
Occlusions, discontinuities, and epipolar lines in stereo
inferred← citeshttps://doi.org/10.1016/j.visres.2005.06.028openalex-snapshot
Illusory volumes in human stereo perception
inferred← citeshttps://doi.org/10.1016/s0031-3203(01)00150-9openalex-snapshot
Junction detection and grouping with probabilistic edge models and Bayesian
inferred← citeshttps://doi.org/10.1109/34.689300openalex-snapshot
Junctions: detection, classification, and reconstruction
inferred← citeshttps://doi.org/10.1109/cvpr.1997.609427openalex-snapshot
On occluding contour artifacts in stereo vision
inferred← citeshttps://doi.org/10.1109/cvpr.1999.786929openalex-snapshot
Multi-scale feature selection in stereo
inferred← citeshttps://doi.org/10.1109/iccv.2001.937544openalex-snapshot
A probabilistic framework for space carving
inferred← citeshttps://doi.org/10.1109/iccv.2003.1238386openalex-snapshot
On exploiting occlusions in multiple-view geometry
inferred← citeshttps://doi.org/10.1109/tip.2002.806242openalex-snapshot
Two bayesian methods for junction classification
inferred← citeshttps://doi.org/10.5244/c.13.25openalex-snapshot
The Applications of Uncalibrated Occlusion Junctions
inferred← citeshttps://doi.org/10.5772/4945openalex-snapshot
Local Feature Selection and Global Energy Optimization in Stereo
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