In this report, different vision-based approaches to solve the problem of hand pose estimation are reviewed. The first three methods presented utilize random forest, whereas the last tackles the problem of pose estimation of two strongly interacting hands. Lastly, an outlook at the future of the field is given. ACM Classification: H5.2 [Information interfaces and presentation]: User Interfaces....

With the development of ubiquitous computing, current user interaction approaches with keyboard, mouse and pen are not sufficient. Due to the limitation of these devices the useable command set is also limited. Direct use of hands as an input device is an attractive method for providing natural Human Computer Interaction which has evolved from text-based interfaces through 2D graphical-based in...

In view of the problem that the accuracy and robustness of hand gesture recognition technology based on vision in the process of using gestures to interact with robots were unstable due to its background, illumination and other factors, this paper presented a gesture segmentation and recognition method Combining depth information and color images. First, it used Kinect sensor to obtain depth in...

In this paper, a novel gesture spotting and recognition technique is proposed to handle hand gesture from continuous hand motion based on Conditional Random Fields in conjunction with Support Vector Machine. Firstly, YCbCr color space and 3D depth map are used to detect and segment the hand. The depth map is to neutralize complex background sense. Secondly, 3D spatio-temporal features for hand ...

Hand gesture recognition system plays a vital role in our day to day life. This hand gesture recognition system provides us natural, innovative, user friendly way of interaction with the computer which is more familiar to us. Gesture recognition has a wide area of application including human machine interaction, sign language, game technology robotics etc. There are different static hand gestur...

In this paper, we introduce a hand gesture recognition system to recognize continuous gesture before stationary background. The system consists of four modules: a real time hand tracking and extraction, feature extraction, hidden Markov model (HMM) training, and gesture recognition. First, we apply a real-time hand tracking and extraction algorithm to trace the moving hand and extract the hand ...

Hand gesture recognition system plays a vital role in our day to day life. This hand gesture recognition system provides us natural, innovative, user friendly way of interaction with the computer which is more familiar to us. Gesture recognition has a wide area of application including human machine interaction, sign language, game technology robotics etc. There are different static hand gestur...

Gestures considered as the most natural expressive way for communications between human and computers in virtual system. Hand gesture is a method of non-verbal communication for human beings for its freer expressions much more other than body parts. Hand gesture recognition has greater importance in designing an efficient human computer interaction system. Using gestures as a natural interface ...

Hand gestures are an important modality for human computer interaction (HCI) [1]. Compared to many existing interfaces, hand gestures have the advantages of being easy to use, natural, and intuitive. Successful applications of hand gesture recognition include computer games control [2], human-robot interaction [3], and sign language recognition [4], to name a few. Vision-based recognition syste...

The goal of static hand gesture recognition is to classify the given hand gesture data represented by some features into some prede ned nite number of gesture classes. The main objective of this e ort is to explore the utility of two feature extraction methods, namely, hand contour and complex moments to solve the hand gesture recognition problem by identifying the primary advantages and disadv...