The proposed work is part of a project that aims at the control of a videogame based on hand gesture recognition. This goal implies the restriction of real-time response and the use of unconstrained environments. In this paper we present a new algorithm to track and recognise hand gestures for interacting with a videogame. This algorithm is based on three main steps: hand segmentation, hand tra...

Visual hand gesture based interfaces have been widely used for navigation of virtual environments and control of a robot arm in robotic systems. In fact, hand movement has abundant powers of expression with complex finger joint motions. In this paper, the full degree-of-freedom hand motion is tracked in a vision-based mode towards natural and intuitive control of a dexterous robotic hand. The m...

This paper presents a method for vision based estimation of the pose of human hands in interaction with objects. Despite the fact that most robotics applications of human hand tracking involve grasping and manipulation of objects, the majority of methods in the literature assume a free hand, isolated from the surrounding environment. Our hand tracking method is non-parametric, performing a near...

A survey of video databases that can be used within a continuous sign language recognition scenario to measure the performance of head and hand tracking algorithms either w.r.t. a tracking error rate or w.r.t. a word error rate criterion is presented in this work. Robust tracking algorithms are required as the signing hand frequently moves in front of the face, may temporarily disappear, or cro...

Hand gesture tracking is one of core method in the field of Human Computer Interaction. In this paper we proposed a tracking method based on Particle Filter framework. Particle Filter algorithm provides a powerful open framework for target tracking and can efficiently deal with motion estimation under the non-linear and nonGaussian environments. The novelty of our method is in the combination o...

In this paper a novel method for moving object tracking is presented and applied in the context of hand tracking for mobile AugmentedReality (AR) applications. AR glasses-like devices come with an integrated camera capturing the field of view of the user. Hand gestures are the most intuitive interaction modality for manipulating AR contents and hand tracking is the first step towards robust ges...

We propose and implement a new method of detecting hand signs by combining skin color detection in transformed 2D normalized RGB or YCbCr color space, PCAbased detection of hand gestures and movement tracking of hand centroids. Hand gesture recognition is a field of research with growing applications, and the implemented system uses movement-tracking pairing for more granular recognition and co...

When we make an aiming movement toward a moving visual object, eye-hand coupling is of paramount importance for accurate motor performance. Some studies have suggested that both gaze and manual tracking control systems are driven by a common command signal. However, it has never been demonstrated that a motor plan for the arm is produced even when the object is tracked by the eyes alone. By app...

We present a novel solution to the problem of recovering and tracking the 3D position, orientation and full articulation of a human hand from markerless visual observations obtained by a Kinect sensor. We treat this as an optimization problem, seeking for the hand model parameters that minimize the discrepancy between the appearance and 3D structure of hypothesized instances of a hand model and...

We address the highly challenging problem of real-time 3D hand tracking based on a monocular RGB-only sequence. Our tracking method combines a convolutional neural network with a kinematic 3D hand model, such that it generalizes well to unseen data, is robust to occlusions and varying camera viewpoints, and leads to anatomically plausible as well as temporally smooth hand motions. For enhancing...