Automatic image segmentation is a challenging task in computer vision applications,
especially in the presence of occluded objects, varying color, and different lighting …

Recent advances in depth imaging sensors provide easy access to the synchronized depth
with color, called RGB-D image. In this paper, we propose an unsupervised method for …

We propose parallel implementation on GPU (graphics processing unit) system for some
generic algorithms applied to superpixel image segmentation problem. The aim is to provide …

In this paper, we introduce a novel graph representation for interactive light field
segmentation using Markov Random Field (MRF). The greatest barrier to the adoption of …

With the introduction of low-cost depth image sensors, reliable image segmentation within
RGB-D images is an ambitious goal of computer vision. However, in a cluttered scene …

We present an approach for segmentation and semantic labelling of RGBD data exploiting
together geometrical cues and deep learning techniques. An initial over‐segmentation is …

In this work, a challenging vehicle type classification problem for automatic toll collection
task is considered, which is currently accomplished with an Optical Sensors (OS) and …

This paper proposes a joint color and depth segmentation scheme exploiting together
geometrical clues and a learning stage. The approach starts from an initial over …

The recent introduction of consumer depth cameras has opened the way to novel
segmentation approaches exploiting depth data together with the color information. This …

This paper proposes a segmentation scheme based on the joint usage of color and depth
data together with a 3D surface estimation scheme. Firstly a set of multi-dimensional vectors …