Ambient Gestures

We present Ambient Gestures, a novel gesture-based system designed to support ubiquitous ‘in the environment’ interactions with everyday computing technology. Hand gestures and audio feedback allow users to control computer applications without reliance on a graphical user interface, and without having to switch from the context of a non-computer task to the context of the computer. The Ambient Gestures system is composed of a vision recognition software application, a set of gestures to be processed by a scripting application and a navigation and selection application that is controlled by the gestures. This system allows us to explore gestures as the primary means of interaction within a multimodal, multimedia environment. In this paper we describe the Ambient Gestures system, define the gestures and the interactions that can be achieved in this environment and present a formative study of the system. We conclude with a discussion of our findings and future applications of Ambient Gestures in ubiquitous computing

Awkward gestures

A consideration of how irreverent approaches to fashion illustration can open a space for more critical approaches to the form - challenging idealised representations of the body, bringing a sense of 'humanness' to fashion or by reflecting on what our preoccupation with fashion says about human nature in the 21st Century. The article focussed on the work of Helen Bullock, Florence Shaw and Damien Florebert Cuypers and included interviews with all three in reference to the article topic. This article was commissioned by Varoom! for their politics themed issue

Selecting a Small Set of Optimal Gestures from an Extensive Lexicon

Finding the best set of gestures to use for a given computer recognition problem is an essential part of optimizing the recognition performance while being mindful to those who may articulate the gestures. An objective function, called the ellipsoidal distance ratio metric (EDRM), for determining the best gestures from a larger lexicon library is presented, along with a numerical method for incorporating subjective preferences. In particular, we demonstrate an efficient algorithm that chooses the best $n$ gestures from a lexicon of $m$ gestures where typically $n \ll m$ using a weighting of both subjective and objective measures.Comment: 27 pages, 7 figure

A robustness verification system for mobile phone authentication based on gestures using Linear Discriminant Analysis

This article evaluates an authentication technique for mobiles based on gestures. Users create a remindful identifying gesture to be considered as their in-air signature. This work analyzes a database of 120 gestures of different vulnerability, obtaining an Equal Error Rate (EER) of 9.19% when robustness of gestures is not verified. Most of the errors in this EER come from very simple and easily forgeable gestures that should be discarded at enrollment phase. Therefore, an in-air signature robustness verification system using Linear Discriminant Analysis is proposed to infer automatically whether the gesture is secure or not. Different configurations have been tested obtaining a lowest EER of 4.01% when 45.02% of gestures were discarded, and an optimal compromise of EER of 4.82% when 19.19% of gestures were automatically rejected

The relation between pitch and gestures in a story-telling task

Anecdotal evidence suggests that both pitch range and gestures contribute to the perception of speakers\u2019 liveliness in speech. However, the relation between speakers\u2019 pitch range and gestures has received little attention. It is possible that variations in pitch range might be accompanied by variations in gestures, and vice versa. In second language speech, the relation between pitch range and gestures might also be affected by speakers\u2019 difficulty in speaking the L2. In this pilot study we compare global pitch range and gesture rate in the speech of 3 native Italian speakers, telling the same story once in Italian and twice in English as part of an in-class oral presentation task. The hypothesis tested is that contextual factors, such as speakers\u2019 nervousness with the task, cause speakers to use narrow pitch range and limited gestures; a greater ease with the task, due to its repetition, cause speakers to use a wider pitch range and more gestures. This experimental hypothesis is partially confirmed by the results of this study

Take Your Seats Performance Symposium

Piano & electronics improvisation to accompany Grand Gestures Dance Collective's performance at Take Your Seats Performance Symposium, Shipley Art Gallery, Gateshead

Rhythmic Micro-Gestures: Discreet Interaction On-the-Go

We present rhythmic micro-gestures, micro-movements of the hand that are repeated in time with a rhythm. We present a user study that investigated how well users can perform rhythmic micro-gestures and if they can use them eyes-free with non-visual feedback. We found that users could successfully use our interaction technique (97% success rate across all gestures) with short interaction times, rating them as low difficulty as well. Simple audio cues that only convey the rhythm outperformed animations showing the hand movements, supporting rhythmic micro-gestures as an eyes-free input technique