hand gesture recognition is very important to communicate in sign language. in this paper, an effective object tracking and hand gesture recognition method is proposed. this method is combination of two well-known approaches, the mean shift and the motion detection algorithm. the mean shift algorithm can track objects based on the color, then when hand passes the face occlusion happens. several...

We present a method for clustering short push-to-talk speech segments in the presence of different numbers of speakers. Iterative Mean Shift algorithm based on the cosine distance is used to perform speaker clustering on i-vectors generated from many short speech segments. We report results as measured by the Accuracy, the average number of detected speakers (ANDS), the average cluster purity (...

This paper presents a robust player tracking method for sports video analysis. In order to track agile player stably and robustly, we employ multiple models method, with a mean shift procedure corresponding to each model for player localization. Furthermore, we define pseudo measurement via fusing the measurements obtained by mean shift procedure. And the fusing coefficients are built from two ...

This paper presents a novel feature set for visual tracking that is derived from “oriented energies”. More specifically, energy measures are used to capture a target’s multiscale orientation structure across both space and time, yielding a rich description of its spatiotemporal characteristics. To illustrate utility with respect to a particular tracking mechanism, we show how to instantiate ori...

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Traditional structure from motion is hard in indoor environments with only a few detectable point features. These environments, however, have other useful characteristics: they often contain severable visible lines, and their layout typically conforms to a Manhattan world geometry. We introduce a new algorithm to cluster visible lines in a Manhattan world, seen from two different viewpoints, in...

To highlight the saliency object clearly from the foreground, we propose a saliency detection method based on global contrast with cluster. Due to the fact that background pixels usually have similar patches, we use cluster analysis to merge the background regions. By using mean shift filter, the background pixels with similar color level are clustered and the saliency calculation can be decrea...

Human tracking is an important function for an automatic surveillance system using a vision sensor. However, it is difficult to identify a human exactly in an image due to the variety of poses. This paper describes a method for automatic human tracking based on face detection using Haar-like features and mean-shift tracking. The method increases its trackability by using multi-viewpoint images....

The Continuously Adaptive Mean Shift Algorithm (CamShift) is an adaptation of the Mean Shift algorithm for object tracking that is intended as a step towards head and face tracking for a perceptual user interface. In this paper, we review the CamShift Algorithm and extend a default implementation to allow tracking in an arbitrary number and type of feature spaces. In order to compute the new pr...

In this paper we discuss about a target tracking algorithm based on Mean Shift and Kalman Filter, which is suitable for high speed moving target tracking. The basic Mean Shift algorithm is described in this paper as well. Although basic Mean Shift algorithm can realize target tracking without arguments or searching all the areas effectively, it has shortcomings which can limit its effectiveness...