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CVPR
2008
IEEE
16 years 4 months ago
Granularity and elasticity adaptation in visual tracking
The observation models in tracking algorithms are critical to both tracking performance and applicable scenarios but are often simplified to focus on fixed level of certain target...
Ming Yang, Ying Wu
3DOR
2010
14 years 9 months ago
Semantics-Driven Approach for Automatic Selection of Best Views of 3D Shapes
We introduce a new framework for the automatic selection of the best views of 3D models. The approach is based on the assumption that models belonging to the same class of shapes ...
Hamid Laga
ESANN
2007
15 years 3 months ago
How to process uncertainty in machine learning?
Uncertainty is a popular phenomenon in machine learning and a variety of methods to model uncertainty at different levels has been developed. The aim of this paper is to motivate ...
Barbara Hammer, Thomas Villmann
HRI
2011
ACM
14 years 5 months ago
Learning to interpret pointing gestures with a time-of-flight camera
Pointing gestures are a common and intuitive way to draw somebody’s attention to a certain object. While humans can easily interpret robot gestures, the perception of human beha...
David Droeschel, Jörg Stückler, Sven Beh...
ECCV
2008
Springer
16 years 3 months ago
Semi-supervised On-Line Boosting for Robust Tracking
Abstract. Recently, on-line adaptation of binary classifiers for tracking have been investigated. On-line learning allows for simple classifiers since only the current view of the ...
Helmut Grabner, Christian Leistner, Horst Bischof