A fast and robust hand-driven 3D mouse

The development of new interaction paradigms requires a natural interaction. This means that people should be able to interact with technology with the same models used to interact with everyday real life, that is through gestures, expressions, voice. Following this idea, in this paper we propose a non intrusive vision based tracking system able to capture hand motion and simple hand gestures. The proposed device allows to use the hand as a "natural" 3D mouse, where the forefinger tip or the palm centre are used to identify a 3D marker and the hand gesture can be used to simulate the mouse buttons. The approach is based on a monoscopic tracking algorithm which is computationally fast and robust against noise and cluttered backgrounds. Two image streams are processed in parallel exploiting multi-core architectures, and their results are combined to obtain a constrained stereoscopic problem. The system has been implemented and thoroughly tested in an experimental environment where the 3D hand mouse has been used to interact with objects in a virtual reality application. We also provide results about the performances of the tracker, which demonstrate precision and robustness of the proposed syste

Evaluation of Physical Finger Input Properties for Precise Target Selection

The multitouch tabletop display provides a collaborative workspace for multiple users around a table. Users can perform direct and natural multitouch interaction to select target elements using their bare fingers. However, physical size of fingertip varies from one person to another which generally introduces a fat finger problem. Consequently, it creates the imprecise selection of small size target elements during direct multitouch input. In this respect, an attempt is made to evaluate the physical finger input properties i.e. contact area and shape in the context of imprecise selection

3DTouch: A wearable 3D input device with an optical sensor and a 9-DOF inertial measurement unit

We present 3DTouch, a novel 3D wearable input device worn on the fingertip for 3D manipulation tasks. 3DTouch is designed to fill the missing gap of a 3D input device that is self-contained, mobile, and universally working across various 3D platforms. This paper presents a low-cost solution to designing and implementing such a device. Our approach relies on relative positioning technique using an optical laser sensor and a 9-DOF inertial measurement unit. 3DTouch is self-contained, and designed to universally work on various 3D platforms. The device employs touch input for the benefits of passive haptic feedback, and movement stability. On the other hand, with touch interaction, 3DTouch is conceptually less fatiguing to use over many hours than 3D spatial input devices. We propose a set of 3D interaction techniques including selection, translation, and rotation using 3DTouch. An evaluation also demonstrates the device's tracking accuracy of 1.10 mm and 2.33 degrees for subtle touch interaction in 3D space. Modular solutions like 3DTouch opens up a whole new design space for interaction techniques to further develop on.Comment: 8 pages, 7 figure

Barehand Mode Switching in Touch and Mid-Air Interfaces

Raskin defines a mode as a distinct setting within an interface where the same user input will produce results different to those it would produce in other settings. Most interfaces have multiple modes in which input is mapped to different actions, and, mode-switching is simply the transition from one mode to another. In touch interfaces, the current mode can change how a single touch is interpreted: for example, it could draw a line, pan the canvas, select a shape, or enter a command. In Virtual Reality (VR), a hand gesture-based 3D modelling application may have different modes for object creation, selection, and transformation. Depending on the mode, the movement of the hand is interpreted differently. However, one of the crucial factors determining the effectiveness of an interface is user productivity. Mode-switching time of different input techniques, either in a touch interface or in a mid-air interface, affects user productivity. Moreover, when touch and mid-air interfaces like VR are combined, making informed decisions pertaining to the mode assignment gets even more complicated. This thesis provides an empirical investigation to characterize the mode switching phenomenon in barehand touch-based and mid-air interfaces. It explores the potential of using these input spaces together for a productivity application in VR. And, it concludes with a step towards defining and evaluating the multi-faceted mode concept, its characteristics and its utility, when designing user interfaces more generally

Vision-Based Finger Detection, Tracking, and Event Identification Techniques for Multi-Touch Sensing and Display Systems

This study presents efficient vision-based finger detection, tracking, and event identification techniques and a low-cost hardware framework for multi-touch sensing and display applications. The proposed approach uses a fast bright-blob segmentation process based on automatic multilevel histogram thresholding to extract the pixels of touch blobs obtained from scattered infrared lights captured by a video camera. The advantage of this automatic multilevel thresholding approach is its robustness and adaptability when dealing with various ambient lighting conditions and spurious infrared noises. To extract the connected components of these touch blobs, a connected-component analysis procedure is applied to the bright pixels acquired by the previous stage. After extracting the touch blobs from each of the captured image frames, a blob tracking and event recognition process analyzes the spatial and temporal information of these touch blobs from consecutive frames to determine the possible touch events and actions performed by users. This process also refines the detection results and corrects for errors and occlusions caused by noise and errors during the blob extraction process. The proposed blob tracking and touch event recognition process includes two phases. First, the phase of blob tracking associates the motion correspondence of blobs in succeeding frames by analyzing their spatial and temporal features. The touch event recognition process can identify meaningful touch events based on the motion information of touch blobs, such as finger moving, rotating, pressing, hovering, and clicking actions. Experimental results demonstrate that the proposed vision-based finger detection, tracking, and event identification system is feasible and effective for multi-touch sensing applications in various operational environments and conditions

Integrating Pointing Gesture Detection for enhancing Brainstorming Meetings using Kinect and PixelSense

AbstractMicrosoft PixelSense is able to detect multitouch input and tagged objects as well, which makes it suitable to be used in net-based brainstorming sessions within small teams. However, any gestures above the table cannot be detected, which makes net-based brainstorming sessions less intuitive. Thus, we present a solution how Kinect can be used together with PixelSense to overcome this limitation without interference between the two devices