Virtual Environment (VE) system offers a natural and intelligent user interface. Hand gesture recognition is more efficient and easier interaction in VE than human-computer interface (HCI) devices like keyboards and mouses. We propose a hand gesture recognition interface that generates commands to control objects directly in a game. Our novel hand gesture recognition system utilizes both Bag-of...

In the past decade, accelerometer sensors became small enough to embed in mobile devices that people are using every day. Thus, arm movements became attractive to control mobile games and game consoles. However, there is no widely-used gesture-vocabulary for controlling devices and gesture recognition is not standardized. Furthermore, there is no widely-accepted benchmark for measuring performa...

In spite of many choices available for gesture recognition algorithms, the selection of a proper algorithm for a specific application remains a difficult task. The available algorithms have different strengths and weaknesses making the matching between algorithms and applications complex. Accurate evaluation of the performance of a gesture recognition algorithm is a cumbersome task. Performance...

The Kinect camera is widely used for capturing human body images and human motion recognition in video game playing, and there are already some research works on gesture recognition. However, to achieve the anti-interference performance, the current recognition algorithms are often complex and tardiness, and most of the applications are based on the incomplete gesture library and not all hand g...

With the rapid emergence of 3D applications and virtual environments in computer systems; the need for a new type of interaction device arises. This is because the traditional devices such as mouse, keyboard, and joystick become inefficient and cumbersome within these virtual environments. In other words, evolution of user interfaces shapes the change in the Human-Computer Interaction (HCI). In...

One of the most important techniques in human-robot communication is gesture recognition. If robots can read intentions from human gestures, the communication process will be smoother and more natural. Processing for gesture recognition typically consists of two parts: feature extraction and gesture classification. In most works, these are independently designed and evaluated by their own crite...

Cyber-physical systems, which closely integrate physical systems and humans, can be applied to a wider range of applications through user movement analysis. In three-dimensional (3D) gesture recognition, multiple sensors are required to recognize various natural gestures. Several studies have been undertaken in the field of gesture recognition; however, gesture recognition was conducted based o...

Automatic gesture recognition, used in humanrobot and human-computer interaction, has been an active area of research for at least three decades, but there are still recurring issues that hinder its application in unconstrained, real-life scenarios. Interpersonal differences in gesture performance present a prominent issue, which limits the gesture recognition process. Furthermore, these differ...

Reliable extraction of human pose features that are invariant to view angle and body shape changes is critical for advancing human movement analysis. In this dissertation, the multifactor analysis techniques, including the multilinear analysis and the multifactor Gaussian process methods, have been exploited to extract such invariant pose features from video data by decomposing various key cont...