(1) Background: Mobile phone use during gait is associated with adverse health outcomes, namely increased risk of pedestrian injury. Healthy individuals can voluntarily prioritize concurrent task performance, but the factors underlying the impact of phone use during walking remain largely unknown. Thus, the objective of this work was to evaluate the relationship between subjective (perceived) prioritization, cognitive flexibility and dual-task performance when using a mobile phone during walking. (2) Methods: Thirty young participants walked for one minute with and without reading or texting on a mobile phone, as well as reading or texting while sitting. Walking performance (kinematics) was recorded, as well as phone use (text comprehension, text read/written), mental workload, perceived prioritization (visual analog scale), and cognitive flexibility (trail-making test). (3) Results: Texting while walking was associated with larger decreases in gait speed, larger gait variability, higher mental workload, and lower text comprehension compared to reading. Perceived prioritization was associated with walking dual-task costs (DTCs) (r = 0.39–0.42, p < 0.04) when texting, and better cognitive flexibility was associated with lower gait DTCs when texting (r = 0.55, p = 0.002) but not reading. (4) Conclusions: The context-dependent link between perceived prioritization, cognitive flexibility, and walking DTCs promotes our understanding of the factors underlying texting-while-walking performance. This could identify individuals who are more prone to dual-task interference in this increasingly common and dangerous task.

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We present a novel system for browsing through a very large set of images according to similarity. The images are dynamically placed on a 2D canvas next to their nearest neighbors in a high-dimensional feature space. The layout and choice of images is generated on-the-fly during user interaction, reflecting the user's navigation tendencies and interests. This intuitive solution for image browsing provides a continuous experience of navigating through an infinite 2D grid arranged by similarity. In contrast to common multidimensional embedding methods, our solution does not entail an upfront creation of a full global map. Image map generation is dynamic, fast and scalable, independent of the number of images in the dataset, and seamlessly supports online updates to the dataset. Thus, the technique is a viable solution for massive and constantly varying datasets consisting of millions of images. Evaluation of our approach shows that when using DynamicMaps, users viewed many more images per minute compared to a standard relevance feedback interface, suggesting that it supports more fluid and natural interaction that enables easier and faster movement in the image space. Most users preferred DynamicMaps, indicating it is more exploratory, better supports serendipitous browsing and more fun to use.

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