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CVPR
1997
IEEE
15 years 11 months ago
Learning Parameterized Models of Image Motion
A framework for learning parameterized models of optical flow from image sequences is presented. A class of motions is represented by a set of orthogonal basis flow fields that ar...
Michael J. Black, Yaser Yacoob, Allan D. Jepson, D...
CAIP
2009
Springer
248views Image Analysis» more  CAIP 2009»
15 years 1 months ago
Rapid Inference of Object Rigidity and Reflectance Using Optic Flow
Abstract. Rigidity and reflectance are key object properties, important in their own rights, and they are key properties that stratify motion reconstruction algorithms. However, th...
Di Zang, Katja Doerschner, Paul R. Schrater
CVPR
1998
IEEE
15 years 11 months ago
Motion Feature Detection Using Steerable Flow Fields
The estimation and detection of occlusion boundaries and moving bars are important and challenging problems in image sequence analysis. Here, we model such motion features as line...
David J. Fleet, Michael J. Black, Allan D. Jepson
SIP
2001
14 years 11 months ago
Estimation of optical flow for large displacements
In this paper we present a new method to estimate optical flow for large displacements. It is based on prediction of global flow field parameters, performs better than multiresolu...
Torsten Radtke, Horst Salzwedel
CVPR
2009
IEEE
16 years 4 months ago
Learning General Optical Flow Subspaces for Egomotion Estimation and Detection of Motion Anomalies
This paper deals with estimation of dense optical flow and ego-motion in a generalized imaging system by exploiting probabilistic linear subspace constraints on the flow. We dea...
Richard Roberts (Georgia Institute of Technology),...