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ICCV
2005
IEEE
16 years 8 months ago
Probabilistic Boosting-Tree: Learning Discriminative Models for Classification, Recognition, and Clustering
In this paper, a new learning framework?probabilistic boosting-tree (PBT), is proposed for learning two-class and multi-class discriminative models. In the learning stage, the pro...
Zhuowen Tu
ICCV
2003
IEEE
16 years 8 months ago
Conditional Feature Sensitivity: A Unifying View on Active Recognition and Feature Selection
The objective of active recognition is to iteratively collect the next "best" measurements (e.g., camera angles or viewpoints), to maximally reduce ambiguities in recogn...
Xiang Sean Zhou, Dorin Comaniciu, Arun Krishnan
ICCV
1999
IEEE
16 years 8 months ago
Neurocalibration: A Neural Network That Can Tell Camera Calibration Parameters
Camera calibration is a primary crucial step in many computer vision tasks. In this paper we present a new neural approach for camera calibration. Unlike some existing neural appr...
Moumen T. Ahmed, Elsayed E. Hemayed, Aly A. Farag
ICCV
1999
IEEE
16 years 8 months ago
Camera Pose and Calibration from 4 or 5 Known 3D Points
We describe two direct quasilinear methods for camera pose (absolute orientation) and calibration from a single image of 4 or 5 known 3D points. They generalize the 6 point `Direc...
Bill Triggs
ICCV
1998
IEEE
16 years 8 months ago
Thresholding for Change Detection
Image differencing is used for many applications involving change detection. Although it is usually followed by a thresholding operation to isolate regions of change there are few...
Paul L. Rosin
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