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» Probabilistic Object Tracking Using Multiple Features
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ICCV
2009
IEEE
15 years 2 months ago
Non-Negative Matrix Factorization of Partial Track Data for Motion Segmentation
This paper addresses the problem of segmenting lowlevel partial feature point tracks belonging to multiple motions. We show that the local velocity vectors at each instant of th...
Anil M. Cheriyadat and Richard J. Radke
MVA
2002
123views Computer Vision» more  MVA 2002»
13 years 9 months ago
Pose Estimation for Insertion of Orbital Replacement Units Against Cluttered Background Using a Non-calibrated Camera
In this paper, we present work from our ongoing project on vision-guided retrieval and insertion of ORUs. Guidance is to be provided through estimated relative poses between an OR...
Chiun-Hong Chien
CVPR
2000
IEEE
14 years 11 months ago
Towards Automatic Discovery of Object Categories
We propose a method to learn heterogeneous models of object classes for visual recognition. The training images contain a preponderance of clutter and learning is unsupervised. Ou...
Markus Weber, Max Welling, Pietro Perona
ATAL
2008
Springer
13 years 11 months ago
Coordination in ambiguity: coordinated active localization for multiple robots
In environments which possess relatively few features that enable a robot to unambiguously determine its location, global localization algorithms can result in multiple hypotheses...
Shivudu Bhuvanagiri, K. Madhava Krishna, Supreeth ...
ICPR
2004
IEEE
14 years 10 months ago
Model Based Object Recognition by Robust Information Fusion
Given a set of 3D model features and their 2D image, model based object recognition determines the correspondences between those features and hence computes the pose of the object...
Haifeng Chen, Ilan Shimshoni, Peter Meer