Pinching sweaters on your phone – iShoogle : multi-gesture touchscreen fabric simulator using natural on-fabric gestures to communicate textile qualities

Abstract

The inability to touch fabrics online frustrates consumers, who are used to evaluating physical textiles by engaging in complex, natural gestural interactions. When customers interact with physical fabrics, they combine cross-modal information about the fabric's look, sound and handle to build an impression of its physical qualities. But whenever an interaction with a fabric is limited (i.e. when watching clothes online) there is a perceptual gap between the fabric qualities perceived digitally and the actual fabric qualities that a person would perceive when interacting with the physical fabric. The goal of this thesis was to create a fabric simulator that minimized this perceptual gap, enabling accurate perception of the qualities of fabrics presented digitally. We designed iShoogle, a multi-gesture touch-screen sound-enabled fabric simulator that aimed to create an accurate representation of fabric qualities without the need for touching the physical fabric swatch. iShoogle uses on-screen gestures (inspired by natural on-fabric movements e.g. Crunching) to control pre-recorded videos and audio of fabrics being deformed (e.g. being Crunched). iShoogle creates an illusion of direct video manipulation and also direct manipulation of the displayed fabric. This thesis describes the results of nine studies leading towards the development and evaluation of iShoogle. In the first three studies, we combined expert and non-expert textile-descriptive words and grouped them into eight dimensions labelled with terms Crisp, Hard, Soft, Textured, Flexible, Furry, Rough and Smooth. These terms were used to rate fabric qualities throughout the thesis. We observed natural on-fabric gestures during a fabric handling study (Study 4) and used the results to design iShoogle's on-screen gestures. In Study 5 we examined iShoogle's performance and speed in a fabric handling task and in Study 6 we investigated users' preferences for sound playback interactivity. iShoogle's accuracy was then evaluated in the last three studies by comparing participants’ ratings of textile qualities when using iShoogle with ratings produced when handling physical swatches. We also described the recording and processing techniques for the video and audio content that iShoogle used. Finally, we described the iShoogle iPhone app that was released to the general public. Our evaluation studies showed that iShoogle significantly improved the accuracy of fabric perception in at least some cases. Further research could investigate which fabric qualities and which fabrics are particularly suited to be represented with iShoogle

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