This paper proposes a method to control an object on a screen by extracting information about a hand with a depth camera. The proposed method employs an appropriate rectangular region, then extracts the hand by setting the arm as a certain size through vector information. The method employs a convex hull to set a reference coordinate of the hand within the coordinate. The object on the screen i...

Discriminative techniques are good for hand part detection, however they fail due to sensor noise and high inter-finger occlusion. Additionally, these techniques do not incorporate any kinematic or temporal constraints. Even though model-based descriptive (for example Markov Random Field) or generative (for example Hidden Markov Model) techniques utilize kinematic and temporal constraints well,...

This paper outlines a system design and implementation of a 3D input device for graphical applications which uses real time hand tracking and gesture recognition to provide the user with an intuitive interface for tomorrow’s applications. Point Distribution Models (PDMs) have been shown to be successful at tracking deformable objects . This system demonstrates how these ‘smart snakes’ can be us...

We propose a real-time model-based 3D hand tracker that combines image regions and the signal from an off-the-shelf 3-axis accelerometer placed on the user’s hand. The visual regions allow the tracker to cope with occlusions, motion blur and background clutter, while the latter aids with the inherent silhouettepose ambiguities. The accelerometer and tracker are synchronised by casting the calib...

In this paper we rst describe how we have constructed a 3D deformable Point Distribution Model of the human hand, capturing training data semi-automatically from volume images via a physically-based model. We then show how we have attempted to use this model in tracking an unmarked hand moving with 6 degrees of freedom (plus deformation) in real time using a single video camera. In the course o...

Hand gestures are important in human communication. It is difficult to transmit visual or spatial concepts only with oral communication (communication human to human) or by regular user interfaces(communication human to machine): keyboard, mouse, etc. The systems of hand gestures recognition are nowadays mainly oriented to the recognition of predefined sets of gestures. This is useful for appli...

3D hand pose tracking/estimation will be very important in the next generation of human-computer interaction. Most of the currently available algorithms rely on low-cost active depth sensors. However, these sensors can be easily interfered by other active sources and require relatively high power consumption. As a result, they are currently not suitable for outdoor environments and mobile devic...

Several sensors have been tested for improving the interaction between humans and machines including traditional web cameras, special gloves, haptic devices, cameras providing stereo pairs of images and range cameras. Meanwhile, several methods are described in the literature for tracking hand motion: the Kalman filter, the mean-shift algorithm and the condensation algorithm. In this research, ...

—We evaluated an automated telemetry system that can dramatically increase the amount of activity and spatial data collected for snakes. We developed methods for analyzing data from single automated receiving units (ARUs) and ARU arrays, compared results from ARUs with conventional hand tracking, and assessed previously untested assumptions used in conventional telemetry, using data from ratsna...

Passive sensing of human hand and limbmotion is important for a wide range of applications from human-computer interaction to athletic performance measurement. High degree of freedom articulated mechanisms like the human hand are di cult to track because of their large state space and complex image appearance. This article describes a model-based hand tracking system, called DigitEyes, that can...