CGF
2010
13 years 8 months ago
2010
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 ...
ICIP
2009
IEEE
13 years 9 months ago
2009
IEEE
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...
SETN
2010
Springer
13 years 9 months ago
2010
Springer
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...
ICPR
2010
IEEE
13 years 9 months ago
2010
IEEE
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...
JUCS
2010
13 years 10 months ago
2010
: 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...
PR
2007
13 years 11 months ago
2007
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...
PAMI
2002
13 years 11 months ago
2002
JMM2
2006
13 years 11 months ago
2006
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 ...
ICPR
2010
IEEE
13 years 12 months ago
2010
IEEE
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...
FGR
2004
IEEE
14 years 3 months ago
2004
IEEE
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...