Superpixels group perceptually similar pixels to create visually meaningful entities while
heavily reducing the number of primitives for subsequent processing steps. As of these …

Several Superpixel segmentation techniques have recently been developed. Superpixels
combine perceptually similar pixels to form visually significant entities, lowering the amount …

Various superpixel approaches have been published recently. These algorithms are
assessed using different evaluation metrics and datasets resulting in discrepancy in …

In this paper we present a method for automatic video segmentation of RGB-D video
streams provided by combined colour and depth sensors like the Microsoft Kinect. To this …

Superpixel algorithms represent a very useful and increasingly popular preprocessing step
for a wide range of computer vision applications, as they offer the potential to boost …

Superpixel segmentation is the oversegmentation of an image into a connected set of
homogeneous regions. Depending on the algorithm, superpixels have specific properties …

In recent years, superpixel algorithms have become a standard tool in computer vision and
many approaches have been proposed. However, different evaluation methodologies make …

Applications are dealing with processing the large data size, especially in satellite multi-
spectral imagery analysis. In fact, many reasons related to security respect, big data or …

To achieve better performance in multifocus image fusion problems, a new regional
approach based on superpixels and superpixel-based mean filtering is proposed in this …

A lot of superpixel algorithms have been proposed in the last decade. Therefore, it is difficult
to select appropriate approaches for specific applications. This page presents results …