In remote mining, operators of complex machinery have more tasks or devices to control than they have hands. For example, operating a rock breaker requires two handed joystick control to position and fire the jackhammer, leaving the camera control to either automatic control or require the operator to switch between controls. We modelled such a teleoperated setting by performing experiments using a simple physical game analogue, being a half size table soccer game with two handles. The complex camera angles of the mining application were modelled by obscuring the direct view of the play area and the use of a Pan-Tilt-Zoom (PTZ) camera. The camera control was via either a keyboard or via head tracking using two different sets of head gestures called "head motion" and "head flicking" for turning camera motion on/off. Our results show that the head motion control was able to provide a comparable performance to using a keyboard, while head flicking was significantly worse. In addition, the sequence of use of the three control methods is highly significant. It appears that use of the keyboard first depresses successful use of the head tracking methods, with significantly better results when one of the head tracking methods was used first. Analysis of the qualitative survey data collected supports that the worst (by performance) method was disliked by participants. Surprisingly, use of that worst method as the first control method significantly enhanced performance using the other two control methods.

/pdf/keyboard-before-head-tracking-depresses-user-success-in-5epsqiu25u.pdf

Keyboard before Head Tracking Depresses User Success in Remote Camera Control

While display quality and rendering for Head-Mounted-Displays (HMDs) has increased in quality and performance, the interaction capabilities with these devices are still very limited or relying on expensive technology. Current experiences offered for mobile HMDs often stick to dome-like looking around, automatic or gaze-triggered movement, or flying techniques. We developed an easy to use walking-in-place technique that does not require additional hardware to enable basic navigation, such as walking, running, or jumping, in virtual environments. Our approach is based on the analysis of data from the inertial unit embedded in mobile HMDs. In a first prototype realized for the Samsung Galaxy Gear VR we detect steps and jumps. A user study shows that users novice to virtual reality easily pick up the method. In comparison to a classic input device, using our walking-in-place technique study participants felt more present in the virtual environment and preferred our method for exploration of the virtual world.

Detecting movement patterns from inertial data of a mobile head-mounted-display for navigation via walking-in-place

Mobile devices such as smartphones, smartwatches or smart glasses have revolutionized how we interact. We are interested in smart glasses because they have the advantage of providing a simultaneous view of both physical and digital worlds. Despite this potential, pointing task on smart glasses is not really widespread. In this paper, we compared four interaction techniques for selecting targets : (a) the Absolute Head Movement and (b) the Relative Head Movement, where head movement controls the cursor on smart glasses in absolute or relative way, (c) the Absolute Free Hand interaction, where the forefinger control the cursor and (d) the Tactile Surface interaction, where the user controls the cursor via a small touchpad connected to smart glasses. We conducted an experiment with 18 participants. The Tactile Surface and Absolute Head Movement were the most efficient. The Relative Head Movement and Absolute Free Hand interactions were promising and require more exploration for other tasks.

Pointing task on smart glasses: Comparison of four interaction techniques

This paper presents mathematical formulae showing that the distance mismatch for an uncentered proof mass in an accelerator sensor does not influence the linearity of the closed-loop accelerometer as a whole. This asymmetry in sensors only introduces an output voltage offset in the readout integrated circuit. Numerical simulation using Matlab/Simulink confirms the mathematical conclusion. The linear response after compensation with a conventional capacitor array is also simulated and analyzed. Results show that there is a loss in linearity. Similar results hold not only for the continuous-time architecture, but also for a time-divided architecture. A readout integrated circuit with a time-divided architecture is designed and fabricated using a 0.35 μm HV CMOS process. An accelerometer composed of a microelectromechanical system sensor with severe built-in distance mismatch and the designed readout integrated circuit is tested. Test results show that the nonlinearity of such accelerometer is within 0.3%.

Linearity analysis of closed-loop capacitive accelerometer due to distance mismatch between plates and the influence of compensation capacitor array

This paper presents a head-tracking system based on an inertial sensor that sends rotation data to an Android application in charge of recording and visualizing data in real time. Data are sent via wireless channel using Bluetooth Low Energy communication and are processed to provide a realistic real-time 3D animation of the user head.

An Android application for head tracking

This work presents a novel user interface for navigation in virtual environments and remote control of devices. The proposed system is head-mounted, allowing for the control of up to six degrees of freedom while leaving the user with free hands. The device is composed of six linear accelerometers arranged on a couple of glasses and a specific embedded controller that allows for the measuring of glass acceleration information. This is then translated in motion control information for navigation in virtual environments and/or as other devices input. The specific algorithms to integrate the motion acceleration cues sensed from the glasses while filtering the drifting errors and effect related to head rotations are presented herein.

A navigation interface based on head tracking by accelerometers

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A navigation interface based on head tracking by accelerometers