Session:「Touch, Pen, and Mice」

Introducing Transient Gestures to Improve Pan and Zoom on Touch Surfaces

論文URL: http://dl.acm.org/citation.cfm?doid=3173574.3173599

論文アブストラクト: Despite the ubiquity of touch-based input and the availability of increasingly computationally powerful touchscreen devices, there has been comparatively little work on enhancing basic canonical gestures such as swipe-to-pan and pinch-to-zoom. In this paper, we introduce transient pan and zoom, i.e. pan and zoom manipulation gestures that temporarily alter the view and can be rapidly undone. Leveraging typical touchscreen support for additional contact points, we design our transient gestures such that they co-exist with traditional pan and zoom interaction. We show that our transient pan-and-zoom reduces repetition in multi-level navigation and facilitates rapid movement between document states. We conclude with a discussion of user feedback, and directions for future research.

日本語のまとめ:

一本の指でタップ状態を保持したままパン,ズーム操作を行い,保持した指を放したときにタップを保持する前の状態に戻ることができる手法を提案した.この手法は従来手法と比べて捜査回数とタスクの完了時間を改善することが分かった.

Pulp Nonfiction: Low-Cost Touch Tracking for Paper

論文URL: http://dl.acm.org/citation.cfm?doid=3173574.3173691

論文アブストラクト: Paper continues to be a versatile and indispensable material in the 21st century. Of course, paper is a passive medium with no inherent interactivity, precluding us from computationally-enhancing a wide variety of paper-based activities. In this work, we present a new technical approach for bringing the digital and paper worlds closer together, by enabling paper to track finger input and also drawn input with writing implements. Importantly, for paper to still be considered paper, our method had to be very low cost. This necessitated research into materials, fabrication methods and sensing techniques. We describe the outcome of our investigations and show that our method can be sufficiently low-cost and accurate to enable new interactive opportunities with this pervasive and venerable material.

日本語のまとめ:

紙の片面を導電層でコーティングし,電解トモグラフィ技術を利用して指と筆記具の両方の紙への入力を追跡することを可能にした.この紙は1枚当たり1ドル以下で作成される.(スライドが誤っています.)

Pentelligence: Combining Pen Tip Motion and Writing Sounds for Handwritten Digit Recognition

論文URL: http://dl.acm.org/citation.cfm?doid=3173574.3173705

論文アブストラクト: Digital pens emit ink on paper and digitize handwriting. The range of the pen is typically limited to a special writing surface on which the pen's tip is tracked. We present Pentelligence, a pen for handwritten digit recognition that operates on regular paper and does not require a separate tracking device. It senses the pen tip's motions and sound emissions when stroking. Pen motions and writing sounds exhibit complementary properties. Combining both types of sensor data substantially improves the recognition rate. Hilbert envelopes of the writing sounds and mean-filtered motion data are fed to neural networks for majority voting. The results on a dataset of 9408 handwritten digits taken from 26 individuals show that motion+sound outperforms single-sensor approaches at an accuracy of 78.4% for 10 test users. Retraining the networks for a single writer on a dataset of 2120 samples increased the precision to 100% for single handwritten digits at an overall accuracy of 98.3%.

日本語のまとめ:

筆記音とペンの傾きをニューラルネットワークで学習し,数字を認識するボールペンPentelligenceを作成した.最終的に全体の認識精度は98.3%,数字一桁の認識精度は100%になった.

Using High Frequency Accelerometer and Mouse to Compensate for End-to-end Latency in Indirect Interaction

論文URL: http://dl.acm.org/citation.cfm?doid=3173574.3174183

論文アブストラクト: End-to-end latency corresponds to the temporal difference between a user input and the corresponding output from a system. It has been shown to degrade user performance in both direct and indirect interaction. If it can be reduced to some extend, latency can also be compensated through software compensation by trying to predict the future position of the cursor based on previous positions, velocities and accelerations. In this paper, we propose a hybrid hardware and software prediction technique specifically designed for partially compensating end-to-end latency in indirect pointing. We combine a computer mouse with a high frequency accelerometer to predict the future location of the pointer using Euler based equations. Our prediction method results in more accurate prediction than previously introduced prediction algorithms for direct touch. A controlled experiment also revealed that it can improve target acquisition time in pointing tasks.

日本語のまとめ:

間接ポインティングにおける遅延を補うために,高性能なマウスと加速度計からの情報を組み合わせてカーソルの位置を予測する.ポインティングタスクを実施し最先端の予測技術と比較した結果,目標獲得時間が改善された.