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Passive navigation as a pattern recognition problem

https://doi.org/10.1007/bf01418980
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What this work says

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

inferredcites →https://doi.org/10.1007/978-3-642-68888-1_11openalex-snapshot
The Measurement of Visual Motion
inferredcites →https://doi.org/10.1007/bf00130488openalex-snapshot
Qualitative detection of motion by a moving observer
inferredcites →https://doi.org/10.1007/bf00137443openalex-snapshot
Relative orientation
inferredcites →https://doi.org/10.1007/bf01450848openalex-snapshot
Qualitative egomotion
inferredcites →https://doi.org/10.1007/bf01469227openalex-snapshot
The role of fixation in visual motion analysis
inferredcites →https://doi.org/10.1016/0004-3702(81)90024-2openalex-snapshot
Determining optical flow
inferredcites →https://doi.org/10.1016/0166-2236(83)90081-4openalex-snapshot
The measurement of visual motion
inferredcites →https://doi.org/10.1016/1049-9660(92)90089-lopenalex-snapshot
Dynamic aspects in active vision
inferredcites →https://doi.org/10.1016/s0734-189x(83)80026-7openalex-snapshot
Passive navigation
inferredcites →https://doi.org/10.1038/293133a0openalex-snapshot
A computer algorithm for reconstructing a scene from two projections
inferredcites →https://doi.org/10.1038/scientificamerican0992-68openalex-snapshot
The Visual Image in Mind and Brain
inferredcites →https://doi.org/10.1098/rspb.1979.0006openalex-snapshot
The interpretation of structure from motion
inferredcites →https://doi.org/10.1098/rspb.1980.0057openalex-snapshot
The interpretation of a moving retinal image
inferredcites →https://doi.org/10.1109/ccv.1988.590022openalex-snapshot
Optimal Computing Of Structure From Motion Using Point Correspondences In Two Frames
inferredcites →https://doi.org/10.1109/pgec.1965.264207openalex-snapshot
An Algorithm for Linear Inequalities and its Applications
inferredcites →https://doi.org/10.1109/tpami.1984.4767471openalex-snapshot
Uniqueness and Estimation of Three-Dimensional Motion Parameters of Rigid Objects with Curved Surfaces
inferredcites →https://doi.org/10.1152/jn.1989.62.3.626openalex-snapshot
Analysis of motion of the visual field by direction, expansion/contraction, and rotation cells clustered in the dorsal part of the medial superior temporal area of the macaque monkey
inferredcites →https://doi.org/10.1152/jn.1991.65.6.1329openalex-snapshot
Sensitivity of MST neurons to optic flow stimuli. I. A continuum of response selectivity to large-field stimuli
inferredcites →https://doi.org/10.1364/josa.66.000717openalex-snapshot
Local structure of movement parallax of the plane
inferredcites →https://doi.org/10.7551/mitpress/1413.003.0014openalex-snapshot
Determining optical flow

What points at this work

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

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Image Analysis and Computer Vision: 1995
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Effects of Errors in the Viewing Geometry on Shape Estimation
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A Critique of Structure-from-Motion Algorithms
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Characterizing Depth Distortion Due to Calibration Uncertainty
inferred← citeshttps://doi.org/10.1007/3-540-61123-1_132openalex-snapshot
Directions of motion fields are hardly ever ambiguous
inferred← citeshttps://doi.org/10.1007/3-540-62909-2_102openalex-snapshot
Motion correspondence through energy minimization
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Motion and Structure from Event-Based Normal Flow
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Bio-inspired Motion Estimation with Event-Driven Sensors
inferred← citeshttps://doi.org/10.1007/bfb0055678openalex-snapshot
What is computed by structure from motion algorithms?
inferred← citeshttps://doi.org/10.1007/s11263-009-0260-yopenalex-snapshot
When Discrete Meets Differential
inferred← citeshttps://doi.org/10.1016/j.cviu.2003.09.003openalex-snapshot
Depth distortion under calibration uncertainty
inferred← citeshttps://doi.org/10.1016/j.cviu.2013.04.007openalex-snapshot
Determining shape and motion from non-overlapping multi-camera rig: A direct approach using normal flows
inferred← citeshttps://doi.org/10.1016/j.patcog.2014.08.012openalex-snapshot
Determining shape and motion from monocular camera: A direct approach using normal flows
inferred← citeshttps://doi.org/10.1016/j.patcog.2020.107759openalex-snapshot
Joint direct estimation of 3D geometry and 3D motion using spatio temporal gradients
inferred← citeshttps://doi.org/10.1016/s0031-3203(99)00084-9openalex-snapshot
Feature matching constrained by cross ratio invariance
inferred← citeshttps://doi.org/10.1016/s0262-8856(99)00082-7openalex-snapshot
Passive navigation using egomotion estimates
inferred← citeshttps://doi.org/10.1023/a:1007928406666openalex-snapshot
Directions of Motion Fields are Hardly Ever Ambiguous
inferred← citeshttps://doi.org/10.1023/a:1008105012585openalex-snapshot
Geometry of Distorted Visual Space and Cremona Transformation
inferred← citeshttps://doi.org/10.1023/a:1012224215211openalex-snapshot
Characterizing Depth Distortion under Different Generic Motions
inferred← citeshttps://doi.org/10.1098/rspb.1997.0112openalex-snapshot
Families of stationary patterns producing illusory movement: insights into the visual system
inferred← citeshttps://doi.org/10.1109/34.615451openalex-snapshot
Robust egomotion estimation from the normal flow using search subspaces
inferred← citeshttps://doi.org/10.1109/cvpr.2000.854927openalex-snapshot
Structure from motion using points, lines, and intensities
inferred← citeshttps://doi.org/10.1109/cvpr52688.2022.00672openalex-snapshot
DiffPoseNet: Direct Differentiable Camera Pose Estimation
inferred← citeshttps://doi.org/10.1109/iccv.1998.710833openalex-snapshot
Egomotion estimation using log-polar images
inferred← citeshttps://doi.org/10.1109/iccv51701.2025.00747openalex-snapshot
Learning Normal Flow Directly from Events
inferred← citeshttps://doi.org/10.1109/icip.2013.6738744openalex-snapshot
Structure from motion directly from a sequence of binocular images without explicit correspondence establishment
inferred← citeshttps://doi.org/10.1109/icip.2013.6738789openalex-snapshot
Binocular estimation of motion: A least-square solution using normal flows
inferred← citeshttps://doi.org/10.1109/icpr.1996.546115openalex-snapshot
Direct egomotion estimation
inferred← citeshttps://doi.org/10.1109/icpr.1998.711080openalex-snapshot
Egomotion estimation on a topological space
inferred← citeshttps://doi.org/10.1109/icpr.2000.905565openalex-snapshot
Direct multi-frame structure from motion for hand-held cameras
inferred← citeshttps://doi.org/10.1109/ijcnn.2016.7727720openalex-snapshot
Theoretical motion functions for video analysis, with a passive navigation example
inferred← citeshttps://doi.org/10.1109/iros.1997.655063openalex-snapshot
Mobile robot navigation using egomotion estimates
inferred← citeshttps://doi.org/10.1109/iros40897.2019.8968520openalex-snapshot
EV-IMO: Motion Segmentation Dataset and Learning Pipeline for Event Cameras
inferred← citeshttps://doi.org/10.1109/iscv.1995.477044openalex-snapshot
Robust and efficient algorithms for optical flow computation
inferred← citeshttps://doi.org/10.1109/iscv.1995.477071openalex-snapshot
The information in the direction of image flow
inferred← citeshttps://doi.org/10.1109/jproc.2002.801440openalex-snapshot
Visual space-time geometry - A tool for perception and the imagination
inferred← citeshttps://doi.org/10.1109/jproc.2014.2347207openalex-snapshot
Contour Motion Estimation for Asynchronous Event-Driven Cameras
inferred← citeshttps://doi.org/10.1109/peeec63877.2024.00185openalex-snapshot
Research and Application of Image Recognition and Automatic Translation Technology in English Translation Software
inferred← citeshttps://doi.org/10.1109/tip.2002.804265openalex-snapshot
Synergizing spatial and temporal texture
inferred← citeshttps://doi.org/10.1126/science.270.5244.1973openalex-snapshot
Direct Perception of Three-Dimensional Motion from Patterns of Visual Motion
inferred← citeshttps://doi.org/10.1177/027836499801700103openalex-snapshot
3D Motion and Shape Representations in Visual Servo Control
inferred← citeshttps://doi.org/10.25911/5d5e73e9e72d2openalex-snapshot
Egomotion estimation with large field-of-view vision
inferred← citeshttps://doi.org/10.5167/uzh-185142openalex-snapshot
EV-IMO: Motion Segmentation Dataset and Learning Pipeline for Event Cameras
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