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CGF
2010
171views more  CGF 2010»
8 years 8 months ago
Efficient Mean-shift Clustering Using Gaussian KD-Tree
Mean shift is a popular approach for data clustering, however, the high computational complexity of the mean shift procedure limits its practical applications in high dimensional ...
Chunxia Xiao, Meng Liu
ICIP
2009
IEEE
8 years 9 months ago
A novel two-tier Bayesian based method for hair segmentation
In this paper, a novel two-tier Bayesian based method is proposed for hair segmentation. In the first tier, we construct a Bayesian model by integrating hair occurrence prior prob...
Dan Wang, Shiguang Shan, Wei Zeng, Hongming Zhang,...
SETN
2010
Springer
8 years 10 months ago
Visual Tracking by Adaptive Kalman Filtering and Mean Shift
A method for object tracking combining the accuracy of mean shift with the robustness to occlusion of Kalman filtering is proposed. At first, an estimation of the object's pos...
Vasileios Karavasilis, Christophoros Nikou, Aristi...
ICPR
2010
IEEE
8 years 10 months ago
Color Connectedness Degree for Mean-Shift Tracking
This paper proposes an extension to the mean shift tracking. We introduce the color connectedness degrees (CCD) which, more than providing statistical information about the target...
Michèle Gouiffès, Florence Laguzet, ...
JUCS
2010
265views more  JUCS 2010»
8 years 10 months ago
A General Framework for Multi-Human Tracking using Kalman Filter and Fast Mean Shift Algorithms
: The task of reliable detection and tracking of multiple objects becomes highly complex for crowded scenarios. In this paper, a robust framework is presented for multi-Human track...
Ahmed Ali, Kenji Terada
PR
2007
293views more  PR 2007»
8 years 11 months ago
Mean shift-based clustering
In this paper, a mean shift-based clustering algorithm is proposed. The mean shift is a kernel-type weighted mean procedure. Herein, we first discuss three classes of Gaussian, C...
Kuo-Lung Wu, Miin-Shen Yang
JMM2
2006
141views more  JMM2 2006»
8 years 12 months ago
Human Tracking by Fast Mean Shift Mode Seeking
Change detection by background subtraction is a common approach to detect moving foreground. The resulting difference image is usually thresholded to obtain objects based on pixel ...
Csaba Beleznai, Bernhard Frühstück, Hors...
ICPR
2010
IEEE
9 years 6 days ago
Improved Mean Shift Algorithm with Heterogeneous Node Weights
The conventional mean shift algorithm has been known to be sensitive to selecting a bandwidth. We present a robust mean shift algorithm with heterogeneous node weights that come f...
Ji Won Yoon, Simon P. Wilson
FGR
2004
IEEE
185views Biometrics» more  FGR 2004»
9 years 3 months ago
Real Time Hand Tracking by Combining Particle Filtering and Mean Shift
Particle filter and mean shift are two successful approaches taken in the pursuit of robust tracking. Both of them have their respective strengths and weaknesses. In this paper, w...
Caifeng Shan, Yucheng Wei, Tieniu Tan, Fréd...
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