Mean shift is a nonparametric estimator of density which has been applied to image and video segmentation. Traditional mean shift based segmentation uses a radially symmetric kernel to estimate local density, which is not optimal in view of the often structured nature of image and more particularly video data. In this paper we present an anisotropic kernel mean shift in which the shape, scale, ...

Two-tier network structure is usually used to lighten the energy consumption in Wireless Multimedia Sensor Networks (WMSNs) for large scale surveillance application. Previous methods for target tracking in two-tier WMSNs mostly focused on reducing energy cost to prolong lifetime of the networks without considering the effect of visual target tracking. This paper presents a collaborative multi-t...

This paper deals with non-rigid object localization in an image, from object colors. Our method allows detection in an image of all the objects which correspond to a color model, without a priori information about their number. Our approach consists in creating a binary image, which represents the repartition of the most probable pixels to be part of the object. Considering this image as a clus...

We discuss a novel statistical framework for image segmentation based on nonparametric clustering. By employing the mean shift procedure for analysis, image regions are identified as clusters in the joint color-spatial domain. To measure the significance of each cluster we use a test statistics that compares the estimated density of the cluster mode with the estimated density on the cluster bou...

We consider applications of clustering techniques, Mean Shift and Self-Organizing Maps, to surface reconstruction (meshing) from scattered point data and review a novel kernel-based clustering method.

Painting style transformation aims to produce a painting in a particular artist’s style from a picture or other paintings. In the previous implementations of example-based painting style transfer, users had to manually select the patches from example patches. It is time-consuming and subjective for a user to select proper patches from a large number of patches. This paper develops a patch-based...

An automatic object tracking and video summarization method for multi-camera systems with a large number of non-overlapping field-of-view cameras is explained. In this framework, video sequences are stored for each object as opposed to storing a sequence for each camera. Objectbased representation enables annotation of video segments, and extraction of content semantics for further analysis. We...