Gesture recognition

2006

The paper addresses the opportunity of using gestures in virtual environments by taking into account current technologies for capturing human gestures, existing interaction techniques and various aspects dealing with gesture and gesticulation functionalities. Virtual environments have proven to be of an effective usefulness for a variety of applications such as medical training and exploration, military simulations, architecture, phobia therapy, etc. A great variety of devices have been developed for effectively interacting with such environments and many interaction techniques have been introduced. Many of them prove to be cumbersome and more or less obstructing the user and hence affecting his/her virtual experience. Natural gestures as a mean of human computer interaction have the great advantage of being the ideal interface as natural, efficient and intuitive means of communication (people use gestures everyday in a natural manner). Discussion is equally conducted on gestures being used for the three main tasks commonly encountered in virtual environments: selection, manipulation and travel. References to gesture definition and classification according to different criteria and their relevance for interacting in virtual environments are equally taken into account.

Computer Game Innovations, 2017

In recent years there has been great progress in virtual reality systems utilizing 6D motion controllers, but there has been relatively little progress in user interfaces taking advantage of this technology. We present a motion gesture recognizer based on an artificial neural network. By utilizing both convolutional and recurrent layers we have developed a system which needs relatively few training samples to label a wide variety of classes. With reduced input feature count our solution provides comparable success rate to traditional hidden Markov model recognizer. This allows to use our system with motion controllers based on internal measurement units.

ACM Transactions on Computer-Human Interaction, 1995

This article presents research-an experiment and the resulting prototype-on a method for treating gestural input so that it can be used for multimodal applications, such as interacting with virtual environments.

2014 International Conference on Computer Graphics Theory and Applications (GRAPP), 2014

Hand-based gestures provide direct mappings of user actions to 3D UI tasks; they are becoming a more attractive interaction alternative than keyboards, mice, controllers, among others. In this paper, we present a fast algorithm for hand gesture recognition for interaction in virtual environments. The method applies mathematical morphology operators (binarization and dilation) to acquire a clean segmented hand image from a depth data stream on which a curvature-metric and K-means algorithm is applied to detect the fingertips, then using fingertip and palm positions together with anthropomorphic metrics and a rule based system we perform gesture recognition. In addition, the intermittence gesture spotting problem is reduced using a digital integrator. Finally, a set of virtual environments were designed to demonstrate the performance, reliability and feasibility of our method.

2011

T h e R e s e a r c h B u l l e t i n o f J o r d a n A C M , I S S N : 2 0 7 8 -7 9 5 2 , V o l u m e I I ( I I I ) P a g e | 86 ABSTRACT 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-offeatures and Support Vector Machine (SVM) to realize user-friendly interaction between human and computers. The HCI based on hand gesture recognition interacts with objects in a 3D virtual environment. With this interface, the user can control and direct a helicopter by a set of hand gesture commands controlling the movements of the helicopter. Our system shows the hand gesture recognition interface can attain an enhanced and more intuitive and flexible interaction for the user than other HCI devices.

Human-Computer Interaction – INTERACT 2021, 2021

We explore gestures as interaction methods in virtual reality (VR). We detect hand and body gestures using human pose estimation based on offthe-shelf optical camera images using machine learning, and obtain reliable gesture recognition without additional sensors. We then employ an avatar to prompt users to learn and use gestures to communicate. Finally, to understand how well gestures serve as interaction methods, we compare the studied gesture-based interaction methods with baseline common interaction modalities in VR (controllers, gaze interaction) in a pilot study including usability testing.

2005

This paper discusses several usability issues related to the use of gestures as an input mode in multimodal interfaces. The use of gestures has been suggested before as a natural solution for applications that require hands-free and notouch interaction with computers, such as in virtual reality (VR) environments. We introduce a simple but robust 2D computer vision based gesture recognition system that was successfully used for interaction in VR environments such as CAVEs and Powerwalls. This interface was tested under 3 different scenarios, as a regular pointing device in a GUI interface, as a navigation tool, and as a visualization tool. Our experiments show that the time to completion of simple pointing tasks is considerably slower when compared to a mouse and that its use during even short periods of time causes fatigue. Despite these drawbacks, the use of gestures as an alternative mode in multimodal interfaces offers several advantages, such as quick access to computing resources that might be embedded in the environment, using a natural and intuitive way, and that scales nicely to group and collaborative applications, where gestures can be used sporadically.

2003

The paper proposes a simple, economical and efficient real-time, visual hand gesture recognition system for human-computer interaction. The system is designed to work in critical lighting conditions, for example when an image is projected onto a wall (conferences, offices, etc). Given the low level of computational complexity, the system can be used instead of a mouse. The extreme naturalness of the interaction makes previous training unnecessary and the robustness of the algorithms used guarantees a high level of reliability. The architecture of the system is described, and experimental results obtained in a large number of tests with different, untrained users are presented and commented.

Functional Plant Science and Biotechnology, 2012

The intent of this article is to review recent literature on plant protease inhibitors which can be divided into different types comprising Kunitz, Bowman-Birk, squash, serine protease and potato inhibitor types. Some of them specifically inhibit trypsin. Others also inhibit chymotrypsin and other proteases. The mode of inhibition can be either competitive or noncompetitive. Some of them are characterized by remarkable thermostability and pH stability. In addition to protease inhibitory activity, antifungal, anti-insect, anticancer and/or HIV-1 reverse transcriptase inhibitory activity are present in some plant protease inhibitors.