Inspired by the adequacy of convolutional neural networks in implicit extraction of visual
features and the efficiency of Long Short-Term Memory Recurrent Neural Networks in dealing …

Object tracking is a computer vision task that aims to locate and continuously follow the
movement of an object in video frames, given an initial annotation. Despite its importance, this …

Speed Up Robust Feature (SURF) and Local Contour Sequence(LCS) are methods used
for feature extraction techniques for dynamic gesture recognition. A problem presented by …

In the last decade, training recurrent neural networks (RNN) using techniques from the area
of reservoir computing (RC) became more attractive for learning sequential data due to the …

Algorithms for hand feature extraction used in gesture recognition systems have some
problems such as unnecessary information gathering. This paper proposes a novel method for …

A computational system able to automatically and efficiently detect and classify falls would
be beneficial for monitoring the elderly population and speed up the assistance proceedings, …

For operating in real world scenarios, the recognition of human gestures must be adaptive,
robust and fast. Despite the prominent use of Kinect-like range sensors for demanding visual …

The true-branching cyanobacterium Fischerella thermalis (also known as Mastigocladus
laminosus) is widely distributed in hot springs around the world. Morphologically, it has been …

In this paper we present a scene understanding approach for assistive robotics based on
learning to recognize different objects from RGB-D devices. Using the depth information it is …

… Ferreira, VA Albuquerque, P. Barros, and BJ Fernandes, “A multimodal approach using …
PABLO BARROS is currently a Research Scientist at the Italian Institute of Technology, Italy. He …