This paper presents a novel hierarchical surface abstraction technique based on Mean Shift for 3D shape matching. The automatically generated statistical modes and their associated geometric properties from Mean Shift-based surface analysis are further integrated into an Attributed Relational Graph (ARG). Therefore, the ARG can be used as an abstract representation of the 3D surface object for ...

A new method for r eal-time tracking of non-rigid objects seen from a moving camera is proposed. The central computational module is based on the mean shift iterations and nds the most probable tar get p osition in the current frame. The dissimilarity between the target model (its c olor distribution) and the target candidates is expr essed by a metric derive d from the Bhattacharyya coe cient....

This paper presents a novel approach for automatic person labelling in video sequences using costumes. The person recognition is carried out by extracting the costumes of all the persons who appear in the video. Then, their reappearance in subsequent frames is performed by searching the reappearance of their costume. Our contribution in this paper is a new approach for costume detection, withou...

segmentation and three‑dimensional (3d) visualization of teeth in dental computerized tomography (ct) images are of dentists’ requirements for both abnormalities diagnosis and the treatments such as dental implant and orthodontic planning. on the other hand, dental ct image segmentation is a difficult process because of the specific characteristics of the tooth’s structure. this paper presents ...

We present a new approach towards efficient and robust tracking by incorporating the efficiency of the mean shift algorithm with the robustness of the particle filtering. The mean shift tracking algorithm is robust and effective when the representation of a target is sufficiently discriminative, the target does not jump beyond the bandwidth, and no serious distractions exist. In case of sudden ...

The Nuchal Translucency thickness measurement is made to identify the Down Syndrome in screening first trimester fetus and presented in this paper. The mean shift analysis and canny operators are utilized for segmenting the nuchal translucency region and the exact thickness has been estimated using Blob analysis. It is observed from the results that the fetus in the 14th week of Gestation is ex...

Outliers and influential observations can have an important effect on work with estimation and inference from establishment survey data. Practical development and implementation of methods to identify and account for outliers and influential observations in complex survey data require an agency to balance several factors, including: (i) the mathematical statistics properties of detection method...

We consider the problem of estimating the gradient lines of a density, which can be used to cluster points sampled from that density, for example via the mean-shift algorithm of Fukunaga and Hostetler (1975). We prove general convergence bounds that we then specialize to kernel density estimation.

Clustering aims at extracting hidden structure in dataset. While the problem of finding compact clusters has been widely studied in the literature, extracting arbitrarily formed elongated structures is considered a much harder problem. In this paper we present a novel clustering algorithm which tackles the problem by a two step procedure: first the data are transformed in such a way that elonga...

The presence of outliers will affect the parameter estimation results and model accuracy. It also occurs in spatial regression model, especially Spatial Autoregressive (SAR) model. is a where effects are attached to dependent variable. Removing analysis eliminate necessary information. Therefore, solution offered modify SAR by giving special treatment observations that have potentially become o...