We propose two approaches to sense tangible objects on capacitive touch screens, which are used in off-the-shelf multi-touch devices such as Apple iPad, iPhone, and 3M's multi-touch displays . We seek for the approaches that do not require modifications to the panels: spatial tag and frequency tag. Spatial tag is similar to fiducial tag used by tangible tabletop surface interaction, and uses multi-point, geometric patterns to encode object IDs. Frequency tag simulates high-frequency touches in the time domain to encode object IDs, using modulation circuits embedded inside tangible objects to simulate high-speed touches in varying frequency. We will show several demo applications. The first combines simultaneous tangible + touch input system. This explores how tangible inputs (e.g., pen, easer, etc.) and some simple gestures work together on capacitive touch panels.

Abstract. Location-aware services can benefit from accurate and reliable indoor location tracking. The widespread adoption of 802.11x wireless LAN as the network infrastructure creates the opportunity to deploy WiFi-based location services with few additional hardware costs. While recent research has demonstrated adequate performance, localization error increases significantly in crowded and dynamic situations due to electromagnetic interferences. This paper proposes collaborative localization as an approach to enhance position estimation by leveraging more accurate location information from nearby neighbors within the same cluster. The current implementation utilizes ZigBee radio as the neighbor-detection sensor. This paper introduces the basic model and algorithm for collaborative localization. We also report experiments to evaluate its performance under a variety of clustering scenarios. Our results have shown 28.2-56% accuracy improvement over the baseline system Ekahau, a commercial WiFi localization system.

Recent research proposes augmenting capacitive touch pads with tangible objects, enabling a new generation of mobile applications enhanced with tangible objects, such as game pieces and tangible controllers. In this paper, we extend the concept to capacitive tangibles consisting of multiple parts, such as stackable gaming pieces and tangible widgets with moving parts. We achieve this using a system of wires and connectors inside each block that causes the capacitance of the bottom-most block to reflect the entire assembly. We demonstrate three types of tangibles, called CapStones, Zebra Dials and Zebra Sliders that work with current consumer hardware and investigate what designs may become possible as touchscreen hardware evolves.Receiving raw capacitance values allows us to distinguish multiple levels of capacitance, which allows us to extract more than a single bit of information per contact. The simple design shown in Figure 11b exploits this. These analog CapStones use only two types of elements: (1) contacts that go straight through and (2) no contact, i.e., simply a blank space. The contacts form a marker that identifies the block.

We present FingerPad, a nail-mounted device that turns the tip of the index finger into a touchpad, allowing private and subtle interaction while on the move. FingerPad enables touch input using magnetic tracking, by adding a Hall sensor grid on the index fingernail, and a magnet on the thumbnail. Since it permits input through the pinch gesture, Fin-gerPad is suitable for private use because the movements of the fingers in a pinch are subtle and are naturally hidden by the hand. Functionally, FingerPad resembles a touchpad, and also allows for eyes-free use. Additionally, since the necessary devices are attached to the nails, FingerPad preserves natural haptic feedback without affecting the native function of the fingertips. Through user study, we analyze the three design factors, namely posture, commitment method and target size, to assess the design of the FingerPad. Though the results show some trade-off among the factors, generally participants achieve 93% accuracy for very small targets (1.2mm-width) in the seated condition, and 92% accuracy for 2.5mm-width targets in the walking condition.

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