Haptic pleasantness, naturalness, and complexity, of geometric raised line drawings

In vision, stimulus pleasantness has been shown to relate to complexity following an inverted U-curve or a linear relationship. At the same time, geometric patterns that are more associated with nature are found to be perceived as more pleasant. However, little is known about how pleasantness relates to naturalness and complexity of tactile geometric patterns. Therefore, we investigated whether haptic pleasantness depends on complexity, and naturalness of a geometric pattern. Because exploratory hand movements have been shown to depend on the haptic property to be extracted and can depend on complexity we also recorded hand movements. We examined the influence of perceived naturalness and complexity on movement speed

Immersive scenes with Radiance in a Virtual Reality Headset: comparison of virtual and real environments

This presentation introduced a novel method for creating immersive scenes for Virtual Reality based on physically-based renderings and discussed the potential and limitation of this method

Virtual reality to assess visual attraction and perceived interest to daylit scene variations

Façades and light pattern composition have been shown to influence the spatial experience and physiological responses of humans [1,2]. The present study examines the effect of sunlight penetration and window size on fixations to the floor of the scene, and the relation between visual interest and fixations in an experiment using 360° scenes displayed in Virtual Reality. One hundred participants were shown the same daylit interior space with varying presence of sun patches (based on sky type and time-of-day variations) and window size in a mixed experimental design. Participants' head movements were recorded during the first 25 seconds of silent free-viewing exposure to each scene, after which they rated the visual interest of the scene. Fixation areas were derived from head movement data and were used to extract the percentage of fixations towards different areas in the scene. Linear Mixed Model (LMM) analyses showed that sun patch presence influenced the percentage of fixations towards both the front part of the floor (near the façade) and the whole floor. Pairwise comparisons showed that participants spent more time fixating towards the floor in the presence of small sun patch compared to no sun patch. Adding visual interest as a fixed factor in the LMM did not show a statistically significant relation between fixations towards the floor and visual interest ratings. Although limited to Virtual Reality and thus to its relatively small luminance range, these findings show that the presence of a sun patch in one's field of view elicits visual attraction

Saliency prediction in 360° architectural scenes:Performance and impact of daylight variations

Saliency models are image-based prediction models that estimate human visual attention. Such models, when applied to architectural spaces, could pave the way for design decisions where visual attention is taken into account. In this study, we tested the performance of eleven commonly used saliency models that combine traditional and deep learning methods on 126 rendered interior scenes with associated head tracking data. The data was extracted from three experiments conducted in virtual reality between 2016 and 2018. Two of these datasets pertain to the perceptual effects of daylight and include variations of daylighting conditions for a limited set of interior spaces, thereby allowing to test the influence of light conditions on human head movement. Ground truth maps were extracted from the collected head tracking logs, and the prediction accuracy of the models was tested via the correlation coefficient between ground truth and prediction maps. To address the possible inflation of results due to the equator bias, we conducted complementary analyses by restricting the area of investigation to the equatorial image regions. Although limited to immersive virtual environments, the promising performance of some traditional models such as GBVS360eq and BMS360eq for colored and textured architectural rendered spaces offers us the prospect of their possible integration into design tools. We also observed a strong correlation in head movements for the same space lit by different types of sky, a finding whose generalization requires further investigations based on datasets more specifically developed to address this question.</p

Saliency prediction in 360° architectural scenes:Performance and impact of daylight variations

Saliency models are image-based prediction models that estimate human visual attention. Such models, when applied to architectural spaces, could pave the way for design decisions where visual attention is taken into account. In this study, we tested the performance of eleven commonly used saliency models that combine traditional and deep learning methods on 126 rendered interior scenes with associated head tracking data. The data was extracted from three experiments conducted in virtual reality between 2016 and 2018. Two of these datasets pertain to the perceptual effects of daylight and include variations of daylighting conditions for a limited set of interior spaces, thereby allowing to test the influence of light conditions on human head movement. Ground truth maps were extracted from the collected head tracking logs, and the prediction accuracy of the models was tested via the correlation coefficient between ground truth and prediction maps. To address the possible inflation of results due to the equator bias, we conducted complementary analyses by restricting the area of investigation to the equatorial image regions. Although limited to immersive virtual environments, the promising performance of some traditional models such as GBVS360eq and BMS360eq for colored and textured architectural rendered spaces offers us the prospect of their possible integration into design tools. We also observed a strong correlation in head movements for the same space lit by different types of sky, a finding whose generalization requires further investigations based on datasets more specifically developed to address this question.</p

Saliency prediction in 360° architectural scenes: Performance and impact of daylight variations

Saliency models are image-based prediction models that estimate human visual attention. Such models, when applied to architectural spaces, could pave the way for design decisions where visual attention is taken into account. In this study, we tested the performance of eleven commonly used saliency models that combine traditional and deep learning methods on 126 rendered interior scenes with associated head tracking data. The data was extracted from three experiments conducted in virtual reality between 2016 and 2018. Two of these datasets pertain to the perceptual effects of daylight and include variations of daylighting conditions for a limited set of interior spaces, thereby allowing to test the influence of light conditions on human head movement. Ground truth maps were extracted from the collected head tracking logs, and the prediction accuracy of the models was tested via the correlation coefficient between ground truth and prediction maps. To address the possible inflation of results due to the equator bias, we conducted complementary analyses by restricting the area of investigation to the equatorial image regions. Although limited to immersive virtual environments, the promising performance of some traditional models such as GBVS360eq and BMS360eq for colored and textured architectural rendered spaces offers us the prospect of their possible integration into design tools. We also observed a strong correlation in head movements for the same space lit by different types of sky, a finding whose generalization requires further investigations based on datasets more specifically developed to address this question

Daylight patterns as a means to influence the spatial ambiance: a preliminary study

This contribution focuses on perforated façades, investigating the effect of the façade and the resulting daylight pattern on the perceived spatial ambiance. The daylight conditions, as well as the geometry and regularity of the façade pattern are manipulated in an immersive virtual space, producing different conditions. A preliminary study was conducted, where subjective evaluations of the virtual space were recorded across six variations of façade pattern and sky type. The results indicate that the façade pattern characteristics have an impact on the perceived spatial ambiance, underlining the need to investigate further the perceptual aspect of the spatial and temporal diversity of light in space through experimental studies