Machine Understanding of Human Behavior

A widely accepted prediction is that computing will move to the background, weaving itself into the fabric of our everyday living spaces and projecting the human user into the foreground. If this prediction is to come true, then next generation computing, which we will call human computing, should be about anticipatory user interfaces that should be human-centered, built for humans based on human models. They should transcend the traditional keyboard and mouse to include natural, human-like interactive functions including understanding and emulating certain human behaviors such as affective and social signaling. This article discusses a number of components of human behavior, how they might be integrated into computers, and how far we are from realizing the front end of human computing, that is, how far are we from enabling computers to understand human behavior

A study on interaction-driven comparison between analog and digital gaming control interface on smartphone

This study aims to find empirical evidence of effectiveness levels: comfort, efficiency, and accuracy between analog and digital interface on smartphone game control through the two different usability tests: 1) A Pilot Study for measuring a correlation contrast with direct and indirect input control from six participants in a small group; 2) A Main Study for finding the effectiveness of “Tap-only affords” basis between a digital and analog input control. The usability test was analyzed by both qualitative and quantitative research methods. There was a total of the 81 participants who were divided into two big groups for comparing one hand and two hands input control, and nine participants per each group implemented a smartphone game based on different input control tasks. The findings appear that direct touch screen interaction is more effective on two hands input control tasks while using an indirect physical input control was more effective on one hand touchscreen

Master Hand Technology For The HMI Using Hand Gesture And Colour Detection

Master Hand Technology uses different hand gestures and colors to give various commands for the Human-Machine(here Computer) Interfacing. Gestures recognition deals with the goal of interpreting human gestures via mathematical algorithm. Gestures made by users with the help of a color band and/or body pose , in two or three dimensions , get translated by software/image processing into predefined commands .The computer then acts according to the command. There have been a lot work already developed in this field either by extracting hand gesture only or extracting hand with the help of color segmentation. In this project, both hand gesture extraction and color detection used for better, faster, robust, accurate and real-time applications. Red, Green, Blue colors are most efficiently detected if RGB color space used. Using HSV color space, it can be extended to any no of colors. For hand gesture detection, the default background is captured and stored for further processing. Comparing the new captured image with background image and doing necessary extraction and filtering, hand portion can be extracted. Then applying different mathematical algorithms different hand gestures detected. All this work done using MATLAB software. By interfacing a portion of Master hand or/and color to mouse of a Computer, the computer can be controlled same as the mouse. And then many virtual (Augmented reality) or PC based application can be developed (e.g. Calculator, Paint). It does not matter whether the system is within your reach or not; but a camera that is linked with the system must have to be near-by . Showing different gestures by your Master-Hand , the computer can be controlled remotely. If the camera can be set-up online, then the computer can be controlled even from a very far place online

Emerging technologies for learning (volume 1)

Collection of 5 articles on emerging technologies and trend