Fig. 1. Experimental design research (right) is one example among many, where augmented and virtual reality technologies are used in combination with eye-tracking. This work addresses how semantic gaze analysis in real-world and virtual-reality settings can be done using convolutional neural networks (left). ©Lena Stubbemann Virtual-reality (VR) and augmented-reality (AR) technology is increasingly combined with eye-tracking. This combination broadens both fields and opens up new areas of application, in which visual perception and related cognitive processes can be studied in interactive but still well controlled settings. However, performing a semantic gaze analysis of eye-tracking data from interactive three-dimensional scenes is a resource-intense task, which so far has been an obstacle to economic use. In this paper we present a novel approach which minimizes time and information necessary to annotate volumes of interest (VOIs) by using techniques from object recognition. To do so, we train convolutional neural networks (CNNs) on synthetic data sets derived from virtual models using image augmentation techniques. We evaluate our method in real and virtual environments, showing that the method can compete with state-of-the-art approaches, while not relying on additional markers or preexisting databases but instead offering cross-platform use.

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Despite its undisputable benefits for firms, crowdsourcing is rarely applied in small and medium sized enterprises (SME), yet. Until today extant literature provides only an uncomplete picture of the barriers that hinder SMEs from adopting crowdsourcing. Because of these incomplete insights on this phenomenon there is a great deal of uncertainty on how to overcome these barriers all the more. In the scope of an interview series with 15 SMEs we explore a range of different barriers. The findings from our study do not only expand the so far incomplete body of knowledge but also provide practical references for SMEs to be aware of the barriers. This simplifies avoiding them and successfully adopting crowdsourcing.

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