Recent findings from Embodied Cognition reveal strong effects of arm and hand movement on spatial memory. This suggests that input devices may have a far greater influence on users' cognition and users' ability to master a system than we typically believeespecially for spatial panning or zooming & panning user interfaces. We conducted two experiments to observe whether multi-touch instead of mouse input improves users' spatial memory and navigation performance for such UIs. We observed increased performances for panning UIs but not for zooming & panning UIs. We present our results, provide initial explanations and discuss opportunities and pitfalls for interaction designers.
Measuring the performance of text recognition and text line detection engines is an important step to objectively compare systems and their configuration. There exist wellestablished measures for both tasks separately. However, there is no sophisticated evaluation scheme to measure the quality of a combined text line detection and text recognition system. The F-measure on word level is a well-known methodology, which is sometimes used in this context. Nevertheless, it does not take into account the alignment of hypothesis and ground truth text and can lead to deceptive results. Since users of automatic information retrieval pipelines in the context of text recognition are mainly interested in the end-to-end performance of a given system, there is a strong need for such a measure. Hence, we present a measure to evaluate the quality of an end-to-end text recognition system. The basis for this measure is the well established and widely used character error rate, which is limited -in its original form -to aligned hypothesis and ground truth texts. The proposed measure is flexible in a way that it can be configured to penalize different reading orders between the hypothesis and ground truth and can take into account the geometric position of the text lines. Additionally, it can ignore over-and under-segmentation of text lines. With these parameters it is possible to get a measure fitting best to its own needs.Index Terms-measure, end-to-end, character error rate, word error rate, F-measure, bag-of-word, HTR
In this paper we present an experiment that aims at understanding the influence that (visual) grid-based structuring of user interfaces can have on spatial and content memory. By the term grid we refer to two different aspects. On the one hand, this relates to the structured alignment, the layout of objects on a canvas. On the other hand, a grid can also be indicated visually by inserting lines that form an array which divides a canvas into smaller fields. In both cases we detected a strong positive influence on spatial memory. On content memory, however, grids have a less beneficial influence. Only if grid lines are visible, the structured alignment has a positive effect. On the other hand, the visibility of grid lines always leads to worse results in content memory performance, independent of the spatial arrangement.
In the VAST Challenge 2009 suspicious behavior had to be detected applying vi s ual analytics to heterogeneous data, such as network traffi~, so~i al network enriched with gco-spatial attributes. and finally video surveillance data. This paper descri bes some of the awarded parts from our sol.ution entry.
Due to advances in technology large displays with very high resolution started to become affordable for daily work. Today it is possible to build display walls with a pixel density that is comparable to standard office screens. Previous work indicates that physical navigation enables a deeper engagement with the data set. In particular, visibility of detailed data subsets on large screens supports users' work and understanding of large data. In contrast to previous work we explore how users' performance scales with an increasing amount of large display space when working with text documents. In a controlled experiment, we determine participants' performance when searching for titles and images in large text documents using one to six 50" 4K monitors. Our results show that the users' visual search performance does not linearly increase with an increasing amount of display space.
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