The Mean Shift tracker is a widely used tool for robustly and quickly tracking the location of
an object in an image sequence using the object's color histogram. The reference histogram …

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, Cauchy …

Cross-bin metrics have been shown to be more suitable than bin-by-bin metrics for
measuring the distance between histograms in various applications. In particular, a visual …

Contemporary research is develo** techniques to tracking objects in videos using color
features, and the mean shift (MS) algorithm is one of the best. This known algorithm is …

Methods for tracking an object have generally fallen into two groups: tracking by detection
and tracking through local optimization. The advantage of detection-based tracking is its …

The subject of mean shift algorithm for tracking the location of an object using a color model
has recently gained considerable interest. However, the use of a color model to represent …

We present a system for the estimation of unconstrained 3D human upper body movement
from multiple cameras. Its main novelty lies in the integration of three components: single …

Kernel-based trackers aggregate image features within the support of a kernel (a mask)
regardless of their spatial structure. These trackers spatially fit the kernel (usually in location …

With the development of machine vision, target trackers based on Siamese networks have
demonstrated excellent performance in balancing speed and accuracy compared to …

This paper proposes a new local texture descriptor, called quad binary pattern (QBP).
Compared with local binary pattern (LBP), the QBP is with stronger robustness for feature …