There is a growing demand to interact with computers in a more natural way. For example using hand gestures to interact with certain type of applications would be more efficient than old-fashioned keyboard and mouse. Hand tracking is one of the key problems in computer vision. We have analyzed many different approaches used for hand tracking. Flocks of features introduced by Mathias Kölsch and ...

Fast and robust hand segmentation and tracking is an essential basis for gesture recognition and thus an important component for contact-less human-computer interaction (HCI). Hand gesture recognition based on 2D video data has been intensively investigated. However, in practical scenarios purely intensity based approaches suffer from uncontrollable environmental conditions like cluttered backg...

There is a growing demand to interact with computers in a more natural way. For example using hand gestures to interact with certain type of applications would be more efficient than old-fashioned mouse and keyboard. To achieve this we need to be able to efficiently track human hand in real-time. We focused on Flocks of Features algorithm introduced by Mathias Kölsch and Matthew Turk, which can...

this paper presents a comparison study between the multilayer perceptron (mlp) and radial basis function (rbf) neural networks with supervised learning and back propagation algorithm to track hand gestures. both networks have two output classes which are hand and face. skin is detected by a regional based algorithm in the image, and then networks are applied on video sequences frame by frame in...

Hand gesture recognition has the potential of simplifying human computer interactions. However, the human hand is a highly articulated object, capable of taking on many different appearances. In this work, we consider an analysis by synthesis approach to this difficult tracking problem. We attempt to overcome the vast amount of computation required by implementing the algorithm on commodity gra...

Visual feedback and non-visual information play different roles in tracking of an external target. This study explored the respective roles of the visual and non-visual information in eleven healthy volunteers who coupled the manual cursor to a rhythmically moving target of 0.5 Hz under three sensorimotor conditions: eye-alone tracking (EA), eye-hand tracking with visual feedback of manual outp...

Compressed sensing is an advanced technique used in visual tracking problem. However, current research uses too many pre-knowledge, and cannot deal with quick object sensitively. Based on the problems, the paper proposes a new real-time visual tracking algorithm based on compressive sensing. On one hand, the algorithm uses the characteristics of compressive sensing, and make sure of the time co...

An eye-in-hand system visually tracking objects can fail when the manipulator encounters a kinematic singularity or a joint limit. A solution to this problem is presented in which objects are visually tracked while the manipulator simultaneously avoids kinematic singularities and manipulator joint limits by moving in directions along which the tracking task space is unconstrained or redundant. ...

We introduce an extension of the self-organizing map for performing 3D hand skeleton tracking. We use a range camera for data acquisition and apply a SOM-like learning process within each frame in order to capture the hand pose. Our method uses a topology consisting of 1D and 2D segments for an improved representation of the hand. The proposed algorithm is very e cient and produces good trackin...

Hand tracking is one of the essential elements in vision based hand gesture recognition system. The tracked hand image can provide a meaningful gesture for more natural ways of Human Computer Interaction (HCI) systems. In this paper, we present a fast hand tracking method based on the fusion of skin and motion features incorporated covariance matrix. First, hand region is detected using a fusio...