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» A Probabilistic Framework for Combining Tracking Algorithms
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ICRA
2010
IEEE
225views Robotics» more  ICRA 2010»
13 years 5 months ago
3D reconstruction of fish schooling kinematics from underwater video
This paper describes a probabilistic framework to estimate the shape and position of multiple fish in a school. We model the fish shape as an ellipsoid with a curvature coefficient...
Sachit Butail, Derek A. Paley
CIKM
2004
Springer
14 years 24 days ago
Unified filtering by combining collaborative filtering and content-based filtering via mixture model and exponential model
Collaborative filtering and content-based filtering are two types of information filtering techniques. Combining these two techniques can improve the recommendation effectiveness....
Luo Si, Rong Jin
IJCV
2002
84views more  IJCV 2002»
13 years 7 months ago
Algorithmic Fusion for More Robust Feature Tracking
We present a framework for merging the results of independent featurebased motion trackers using a classification based approach. We demonstrate the efficacy of the framework usin...
Brendan McCane, Ben Galvin, Kevin Novins
CLEF
2008
Springer
13 years 9 months ago
The Xtrieval Framework at CLEF 2008: Domain-Specific Track
This article describes our participation at the Domain-Specific track. We used the Xtrieval framework [2], [3] for the preparation and execution of the experiments. The translatio...
Jens Kürsten, Thomas Wilhelm, Maximilian Eibl
JMM2
2006
146views more  JMM2 2006»
13 years 7 months ago
Probabilistic Algorithms, Integration, and Empirical Evaluation for Disambiguating Multiple Selections in Frustum-Based Pointing
There are a few fundamental pointing-based user interface techniques for performing selections in 3D environments. One of these techniques is ray pointing, which makes selections b...
Greg S. Schmidt, Dennis G. Brown, Erik B. Tomlin, ...