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ABCDEFEAD ABCDEFEAD ABCCDC !ABEBCA "EC'A EA9D!C-DE!!D ADABD(BCA BA%FCEC$C3!C%$D #BCEADD%C3G!A$ ECBCDBCA F*BA'D+CAD-FC C! #CDCCDD(BCA EC,BEA4C#DC E!DCCFA$ -B)BAD-FC &BCA CDB#DD(BCA .BC.+AD-FC 4%DF BAC.AD*EC7!$5D #DDABEDDACD(BCA /#AD-FC 2DDCA$ BA%'B!CEEE8DD DACBEBDA%DD(BCA -B0A%%01EE8DD ACCB23A1C4%DF ECCBCA 4CABEBE4C#DC E!DCCFA$ BCA BCEBDEA9D!C-DE!!D ABCDEFEAD FDDA ABCDEFEAD ABCDEFFCDE ABCDEFEAD EFDD DCD"#$ ABCDEFEAD ABCDEFEAD Airwriting: Mobile text-entry by 3d-space handwriting Christoph Amma, Marcus Georgi, Tanja Schultz Karlsruhe Institute of Technology (KIT) Cognitive Systems Lab {christoph.amma, tanja.schultz}@kit.edu, [email protected] Abstract We demonstrate a wearable text-entry system. Users can write text in the air, as if they were writing on an imaginary blackboard. Motion is sensed by inertial sensors attached to the back of the hand. Written text is spotted and recognized by a two-stage approach using SVMs and HMMs. The sys- tem works in a person-independent manner and is capable of recognizing text written in block capital letters at natural Figure 1. System usage illustration showing writing speeds without any pauses. the wireless data glove with all components. 1. Demonstration System make any artificial pauses to explicitely mark character or word boundaries. All handwriting must be in block capi- tal letters and should be done in place, i.e. no motion from This paper describes the demonstration of our airwriting left to right is necessary. The size of the characters writ- input system introduced in the accompanying paper [2]. Ac- ten should be approximately 20 cm in height, but the sys- celerometers and Gyroscopes on the back of the hand mea- tem usually still gives good results if the height is between sure hand motion and the written text is recognized based 5 cm to 40 cm. Writing speed can vary as well, in our exper- on the acquired sensor signals. Other approaches to 3d- iment with 9 unexperienced users we observed an average space handwriting recognition have been proposed but are rate of 72 characters per minute, whereas an experienced restricted to single characters or short single words, since user reached 110 CPM. The decoder continuously outputs they rely on the estimation of the actual trajectory and there- the hypothesis with the most probable sentence given the fore suffer from sensor errors accumulating over time [1, 3]. signals received so far. If the user stops to write for a cer- Figure 1 shows our data glove with the inertial measure- tain amount of time (approx. 2 s), the spotting stage detects ment unit attached to the back of the hand. The sensor the end of the handwriting motion which leads to the output data is sent wirelessly to a laptop where all processing takes of the final hypothesis. The system works in an always-on place. We use a two-stage approach for spotting and recog- manner, if the user starts writing again, the decoding starts nizing handwriting. In the first stage, a SVM-based classi- from the beginning. fier detects signal segments that are likely to contain hand- writing. Only those segments are passed on to the second stage, in which the actual text is recognized. In the second References stage HMMs are used to model characters and words and a statistical 3-gram language model is used to model the [1] S. Agrawal, I. Constandache, S. Gaonkar, R. Roy Choudhury, probabilities of certain word sequences. This allows for the K. Caves, and F. DeRuyter. Using mobile phones to write in recognition of whole sentences. The vocabulary of the rec- air. In MobiSys, 2011. [2] C. Amma, M. Georgi, and T. Schultz. Airwriting: Hands-free ognizer contains more than 8000 words. A user can write Mobile Text Input by Spotting and Continuous Recognition of arbitrary sentences formed out of the words contained in 3d-Space Handwriting with Inertial Sensors. In ISWC, 2012. the vocabulary. We reach an average person-independent [3] W.-C. Bang, W. Chang, K.-H. Kang, E.-S. Choi, A. Potanin, word error rate of 11% in a nine user experiment. Users and D.-Y. Kim. Self-contained spatial input device for wear- can write in one continuous motion, they do not need to able computers. ISWC, 2003. ABCDEFEAD Icebreaker T-shirt: a Wearable Device for Easing Face-to-Face Interaction Nanda Khaorapapong Matthew Purver Queen Mary University of London, UK Queen Mary University of London, UK [email protected] [email protected] Abstract enhance comfort and relaxations when meeting strangers, thus helping the wearer select new This paper discusses the development of Icebreaker acquaintances while maintaining the naturalness of the T-shirt with results from an experiment with shy users. social interaction and comforting property of clothing. Embedded with a set of Radio Frequency Identification 1. Introduction (RFID) reader and tag on the cuff of its long-sleeve, the shirt allows two wearers to exchange identities Initiating a conversation is a common challenge for when shaking hands. Next to the RFID system, there is shy people; here, we introduce the Icebreaker T-shirt, a microcontroller designed to retrieve their public designed to be worn in real-world social events, and profile and preference from their Facebook pages via a aimed at increasing comfort feeling and familiarity smartphone (this feature was left out, and information between strangers by leveraging online social network of test subjects was pre-stored in the microcontroller information e.g.