Recognizing manipulations performed by a human and the transfer and execution of this by
a robot is a difficult problem. We address this in the current study by introducing a novel …

Phase-based optical flow algorithms are characterized by high precision and robustness,
but also by high computational requirements. Using the CUDA platform, we have …

Recent years have seen considerable progress in low level image processing as well as
model based, vision applications. Joining the two fields proves to be a difficult problem due …

In this paper, we describe a real-time vision machine having a stereo camera as input
generating visual information on two different levels of abstraction. The system provides …

In this study we present an approach to detecting, describing and tracking independently
moving objects (IMOs) in stereo video sequences acquired by on-board cameras on a …

We present a new method for segmenting color images into their composite surfaces by
combining color segmentation with model-based fitting utilizing sparse depth data, acquired …

Accurate motion analysis of real life sequences is a very active research field due to its
multiple potential applications. Currently, new technologies offer us very fast and accurate …

Local features such as phase, energy and orientation have been widely used in the
literature for multiple computer vision applications such as edge detection, texture analysis …

A novel real-time framework for model-free stereo-video segmentation and stereo-segment
tracking is presented, combining real-time optical flow and stereo with image segmentation …

Model-free tracking is important for solving tasks such as moving-object tracking and action
recognition in cases where no prior object knowledge is available. For this purpose, we …