This chapter presents a method for vote-based 3D shape recognition and registration, in particular using mean shift on 3D pose votes in the space of direct similarity transformations for the first time. We introduce a new distance between poses in this space—the SRT distance. It is left-invariant, unlike Euclidean distance, and has a unique, closed-form mean, in contrast to Riemannian distance,...

The generalized density is a product of a density function and a weight function. For example, the average local brightness of an astronomical image is the probability of finding a galaxy times the mean brightness of the galaxy. We propose a method for studying the geometric structure of generalized densities. In particular, we show how to find the modes and ridges of a generalized density func...

Video segmentation has drawn increasing interest in multimedia applications. This paper proposes a novel joint space-time-range domain adaptive mean shift filter for video segmentation. In the proposed method, segmentation of moving/static objects/background is obtained through interframe mode-matching in consecutive frames and motion vector mode estimation. Newly appearing objects/regions in t...

In this paper, we report the results of a comparative study on skin-color models generally used for facial region location. These include two 2D Gaussian models developed in normalized RGB and HSV color spaces respectively, a 1D lookup table model of hue histogram, and an adaptive 3D threshold box model. Also, we present a new model called “adaptive hue lookup table”. The model is developed by ...

The tracking accuracy of mean shift algorithm employing the Bhattacharyya coefficient as similarity metric is low. The reason is analyzed on the basis of effect identity of the histogram bins in the target model and the candidate. A novel weighting method which is derived from the enhanced histogram intersection is proposed. Several improvements are considered in the implementation of the algor...

In this paper, we describe a Continuously Adaptive Mean Shift (CAMshift) algorithm with a Kalman filter. A CAMshift algorithm does not consider an object’s direction vectors and velocity. In addition, sometimes, CAMshift loses the tracked object when the color of the background is similar to that of the object. However, using a Kalman filter with the CAMshift algorithm can overcome these disadv...

Mean shift algorithms are among the most functional tracking methods which are accurate and have almost simple computation. Different versions of this algorithm are developed which are differ in template updating and their window sizes. To measure the reliability and accuracy of these methods one should normally rely on visual results or number of iteration. In this paper we introduce two new p...

We propose the segmentation of noisy datasets into Multiple Inlier Structures with a new Robust Estimator (MISRE). The scale of each individual structure is estimated adaptively from the input data and refined by mean shift, without tuning any parameter in the process, or manually specifying thresholds for different estimation problems. Once all the data points were classified into separate str...

In statistical process control, the primary method used to monitor the number of nonconformities is the c-chart. The conventional c-chart is based on the assumption that the occurrence of nonconformities in samples is well modeled by a Poisson distribution. When the Poisson assumption is not met, the X-chart (individuals chart) is often used as an alternative charting scheme in practice. In thi...

The traditional color-based mean-shift tracking algorithm is popular among tracking methods due to its simple and efficient procedure, however, the lack of dynamism in its target model makes it unsuitable for tracking objects which have changes in their sizes and shapes. In this paper, we propose a fast novel threephase colored object tracker algorithm based on mean shift idea while utilizing a...