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» Robust Computer Vision through Kernel Density Estimation
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103
Voted
CVPR
2006
IEEE
16 years 3 months ago
Tunable Kernels for Tracking
We present a tunable representation for tracking that simultaneously encodes appearance and geometry in a manner that enables the use of mean-shift iterations for tracking. The cl...
Vasu Parameswaran, Visvanathan Ramesh, Imad Zoghla...
116
Voted
ICCV
2005
IEEE
16 years 3 months ago
Multi-Scale Gesture Recognition from Time-Varying Contours
A novel method is introduced to recognize and estimate the scale of time-varying human gestures. It exploits the changes in contours along spatio-temporal directions. Each contour...
Hong Li, Michael A. Greenspan
128
Voted
ICCV
2007
IEEE
16 years 3 months ago
Variational Segmentation using Fuzzy Region Competition and Local Non-Parametric Probability Density Functions
We describe a novel variational segmentation algorithm designed to split an image in two regions based on their intensity distributions. A functional is proposed to integrate the ...
Benoit Mory, Roberto Ardon, Jean-Philippe Thiran
141
Voted
ICPR
2008
IEEE
15 years 8 months ago
Orientation and scale invariant mean shift using object mask-based kernel
In this paper, we propose a new method for object tracking based on mean shift algorithm using a kernel which has the shape of the target object, and with probabilistic estimation...
Kwang Moo Yi, Ho Seok Ahn, Jin Young Choi
111
Voted
ICPR
2006
IEEE
16 years 3 months ago
Robust Head Pose Estimation Using LGBP
In this paper, we introduce a novel discriminative feature which is efficient for pose estimation. The multi-view face representation is based on Local Gabor Binary Patterns(LGBP)...
Bingpeng Ma, Wenchao Zhang, Shiguang Shan, Xilin C...