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Motion recovery from image sequences using only first order optical flow information
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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/bf00127823openalex-snapshot
Closed-form solutions to image flow equations for 3D structure and motion
inferredcites →https://doi.org/10.1007/bf00127824openalex-snapshot
Motion fields are hardly ever ambiguous
inferredcites →https://doi.org/10.1007/bf00128525openalex-snapshot
Epipolar-plane image analysis: An approach to determining structure from motion
inferredcites →https://doi.org/10.1007/bf00133032openalex-snapshot
Kalman filter-based algorithms for estimating depth from image sequences
inferredcites →https://doi.org/10.1016/0004-3702(81)90024-2openalex-snapshot
Determining optical flow
inferredcites →https://doi.org/10.1016/0734-189x(83)90097-xopenalex-snapshot
Rigid body motion from depth and optical flow
inferredcites →https://doi.org/10.1016/0734-189x(83)90098-1openalex-snapshot
Processing translational motion sequences
inferredcites →https://doi.org/10.1016/0734-189x(86)90076-9openalex-snapshot
Closed from solutions to image flow equations for planar surfaces in motion
inferredcites →https://doi.org/10.1016/0734-189x(89)90035-2openalex-snapshot
A direct method for locating the focus of expansion
inferredcites →https://doi.org/10.1016/0734-189x(90)90151-kopenalex-snapshot
Bounds on time-to-collision and rotational component from first-order derivatives of image flow
inferredcites →https://doi.org/10.1016/0921-8890(91)90036-kopenalex-snapshot
Relative 3D-state estimation for autonomous visual guidance of road vehicles
inferredcites →https://doi.org/10.1016/s0734-189x(85)90146-xopenalex-snapshot
Tracing planar surface motion from a projection without knowing the correspondence
inferredcites →https://doi.org/10.1016/s0734-189x(85)90147-1openalex-snapshot
Detecting the motion of a planar surface by line and surface integrals
inferredcites →https://doi.org/10.1037/h0023863openalex-snapshot
Optical motions and space perception: An extension of Gibson's analysis.
inferredcites →https://doi.org/10.1098/rspb.1980.0057openalex-snapshot
The interpretation of a moving retinal image
inferredcites →https://doi.org/10.1098/rspb.1984.0088openalex-snapshot
The visual ambiguity of a moving plane
inferredcites →https://doi.org/10.1109/34.24780openalex-snapshot
Inherent ambiguities in recovering 3-D motion and structure from a noisy flow field
inferredcites →https://doi.org/10.1109/c-m.1981.220561openalex-snapshot
Visually Interpreting the Motion of Objects in Space
inferredcites →https://doi.org/10.1109/iccv.1990.139501openalex-snapshot
Shape and motion without depth
inferredcites →https://doi.org/10.1109/iccv.1990.139502openalex-snapshot
Simple method for computing 3D motion and depth
inferredcites →https://doi.org/10.1109/tassp.1982.1163931openalex-snapshot
Estimating three-dimensional motion parameters of a rigid planar patch, II: Singular value decomposition
inferredcites →https://doi.org/10.1109/tpami.1983.4767345openalex-snapshot
Direct Computation of the Focus of Expansion
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/10.1109/tpami.1984.4767558openalex-snapshot
Determining Motion Parameters for Scenes with Translation and Rotation
inferredcites →https://doi.org/10.1109/tpami.1985.4767678openalex-snapshot
Determining Three-Dimensional Motion and Structure from Optical Flow Generated by Several Moving Objects
inferredcites →https://doi.org/10.1109/tpami.1986.4767755openalex-snapshot
Estimation of Object Motion Parameters from Noisy Images
inferredcites →https://doi.org/10.1117/12.20003openalex-snapshot
Time-sequential structure and motion estimation without optical flow
inferredcites →https://doi.org/10.1177/027836498500400306openalex-snapshot
Surface Structure and Three-Dimensional Motion from Image Flow Kinematics
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Direct Computation of the FOE with Confidence Measures
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Region-Based Tracking in Video Sequences Using Planar Perspective Models
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Robust egomotion estimation from affine motion parallax
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Optical flow estimation: Advances and comparisons
inferred← citeshttps://doi.org/10.1007/3-540-60793-5_66openalex-snapshot
Direct model-based image motion segmentation for dynamic scene analysis
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An Integrated Neural and Algorithmic System for Optical Flow Computation
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The Role of Theory in the Evaluation of Image Motion Algorithms
inferred← citeshttps://doi.org/10.1007/bf00131147openalex-snapshot
Computation and analysis of image motion: A synopsis of current problems and methods
inferred← citeshttps://doi.org/10.1007/bf01216818openalex-snapshot
Uncalibrated obstacle detection using normal flow
inferred← citeshttps://doi.org/10.1007/bf01451744openalex-snapshot
Optical flow estimation and the interaction between measurement errors at adjacent pixel positions
inferred← citeshttps://doi.org/10.1007/bfb0028339openalex-snapshot
Active camera self-orientation using dynamic image parameters
inferred← citeshttps://doi.org/10.1007/bfb0028363openalex-snapshot
Motion boundary detection in image sequences by local stochastic tests
inferred← citeshttps://doi.org/10.1007/s001380050070openalex-snapshot
Classification and segmentation of vector flow fields using a neural network
inferred← citeshttps://doi.org/10.1007/s10851-006-9001-9openalex-snapshot
A New Parallel Differential Method for Optical Flow Estimation
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3-D motion estimation from motion field
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Estimation of optical flow based on higher-order spatiotemporal derivatives in interlaced and non-interlaced image sequences
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ALTRUISM: Interpretation of three-dimensional information for autonomous vehicle control
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3-D motion estimation by integrating visual cues in 2-D multi-modal opti-acoustic stereo sequences
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Adjustable linear models for optic flow based obstacle avoidance
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An integrated neuromimetic architecture for direct motion interpretation in the log-polar domain
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Exploring parallel capabilities of an innovative numerical method for recovering image velocity vectors field
inferred← citeshttps://doi.org/10.1016/j.visres.2004.05.012openalex-snapshot
Effect of background motion on the perceived shape of a 3-D object
inferred← citeshttps://doi.org/10.1016/s0031-3203(97)00031-9openalex-snapshot
Contour motion estimation from image sequences using curvature information
inferred← citeshttps://doi.org/10.1016/s0042-6989(03)00181-0openalex-snapshot
Recovering slant and angular velocity from a linear velocity field: modeling and psychophysics
inferred← citeshttps://doi.org/10.1016/s0262-8856(00)00060-3openalex-snapshot
Iterative computation of 3D plane parameters
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Contour matching: a curvature-based approach
inferred← citeshttps://doi.org/10.1016/s0898-1221(03)80029-9openalex-snapshot
Regularization of optical flow with M-band wavelet transform
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Chapter 14 General theory of geometric estimation
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Gradient Based Image Motion Estimation Without Computing Gradients
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Dynamic Vergence Using Log-Polar Images
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Robust Optical Flow Computation Based on Least-Median-of-Squares Regression
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On the Fourier Properties of Discontinuous Motion
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Time-to-collision from first-order models of the motion field
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Motion-based grouping of optical flow fields: the extrapolation and subtraction technique
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Depth-from-motion estimation based on a multiscale analysis of motion constraint equation validity
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A simple feedforward neural network architecture for 3-D motion and structure estimation
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Estimation of time-to-collision maps from first order motion models and normal flows
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Positioning a camera parallel to a plane using dynamic visual servoing
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Navigation of a mobile robot on the temporal development of the optic flow
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Recursive estimation of 3D motion and surface structure from local affine flow parameters
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Motion recovery from image sequences using First-order optical flow information
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DETECTION OF SMALL AND SLOW MOVING OBJECTS OBSERVED BY A MOBILE CAMERA
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Camera Motion Determination from Dymanic Perceptual Grouping of Line Segments
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