Abstract. We present a novel approach to segmenting video using iterated graph cuts based on spatio-temporal volumes. We use the mean shift clustering algorithm to build the spatio...
We address the problem of seeking the global mode of a density function using the mean shift algorithm. Mean shift, like other gradient ascent optimisation methods, is susceptible...
Chunhua Shen, Michael J. Brooks, Anton van den Hen...
Mean shift based feature space analysis has been shown to be an elegant, accurate and robust technique. The elegance in this non-parametric algorithm is mainly due to its simplici...
Automatic counting of people, entering or exiting a region of interest, is very important for both business and security applications. This paper introduces an automatic and robus...
The mean shift algorithm is widely applied for nonparametric clustering in Euclidean spaces. Recently, mean shift was generalized for clustering on matrix Lie groups. We further e...
When the appearances of the tracked object and surrounding background change during tracking, fixed feature space tends to cause tracking failure. To address this problem, we prop...
Abstract. This paper presents a novel nonparametric clustering algorithm called evolving mean shift (EMS) algorithm. The algorithm iteratively shrinks a dataset and generates well ...
This paper proposes a novel recombination scheme for evolutionary algorithms, which can guide the new population generation towards the maximum increase of the objective function....
We show that the complexity of the recently introduced medoid-shift algorithm in clustering N points is O(N2 ), with a small constant, if the underlying distance is Euclidean. This...
A nonparametric estimator of density gradient, the mean shift, is employed in the joint, spatial-range (value) domain of gray level and color images for discontinuity preserving l...