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» A Computational Framework for Handling Motion
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ICPR
2002
IEEE
14 years 9 months ago
4-D Voting for Matching, Densification and Segmentation into Motion Layers
* We present a novel approach for grouping from motion, based on a 4-D Tensor Voting computational framework. From sparse point tokens in two frames we recover the dense velocity f...
Gérard G. Medioni, Mircea Nicolescu
AMS
2005
Springer
107views Robotics» more  AMS 2005»
14 years 1 months ago
Elastic View Graphs: A new Framework for Sequential 3D-SLAM
This paper presents a new approach for incremental 3D SLAM from segmented range images with unknown feature association. For feature and motion tracking, an any-time interpretation...
Peter Kohlhepp, Marcus Walther
DAGM
2007
Springer
13 years 11 months ago
Simultaneous Estimation of Surface Motion, Depth and Slopes Under Changing Illumination
Abstract In this paper we extend a multi-camera model for simultaneous estimation of 3d position, normals, and 3d motion of surface patches [17] to be able to handle brightness cha...
Tobias Schuchert, Hanno Scharr
CVPR
2008
IEEE
14 years 10 months ago
What can missing correspondences tell us about 3D structure and motion?
Practically all existing approaches to structure and motion computation use only positive image correspondences to verify the camera pose hypotheses. Incorrect epipolar geometries...
Christopher Zach, Arnold Irschara, Horst Bischof
ICMLA
2007
13 years 9 months ago
Uncertainty optimization for robust dynamic optical flow estimation
We develop an optical flow estimation framework that focuses on motion estimation over time formulated in a Dynamic Bayesian Network. It realizes a spatiotemporal integration of ...
Volker Willert, Marc Toussaint, Julian Eggert, Edg...