Ingrid Heynderickx

Depth of Field Affects Perceived Depth in Stereographs

Although it has been reported that depth of field influences depth perception in nonstereo photographs, it remains unclear how depth of field affects depth perception under stereo viewing conditions. We showed participants stereo photographs with different depths of field using a Wheatstone stereoscope and a commercially available 3D TV. The depicted scene contained a floor, a background, and a measuring probe at different locations. Participants drew a floor plan of the depicted scene to scale. We found that perceived depth decreased with decreasing depth of field for shallow depths of field in scenes containing a height-in-the-field cue. For larger depths of field, different effects were found depending on the display system and the viewing distance. There was no effect on perceived depth using the 3D TV, but perceived depth decreased with increasing depth of field using the Wheatstone stereoscope. However, in the 3D TV case, we found that the perceived depth decreased with increasing depth of field in scenes in which the height-in-the-field cue was removed. This indicates that the effect of depth of field on perceived depth may be influenced by other depth cues in the scene, such as height-in-the-field cues.

Crowdsourcing Empathetic Intelligence: The Case of the Annotation of EMMA Database for Emotion and Mood Recognition

Unobtrusive recognition of the users mood is an essential capability for affect-adaptive systems. Mood is a subtle, long-term affective state, often misrecognized even by humans. The challenge to train a machine to recognize it from, for example, a video of the user, is significant, and already begins with the lack of ground truth for supervised learning. Existing affective databases consist mainly of short videos, annotated in terms of expressed emotions rather than mood. In very few cases, we encounter perceived mood annotations, of questionable reliability, however, due to the subjectivity of mood estimation and the small number of coders involved. In this work, we introduce a new database for mood recognition from video. Our database contains 180 long, acted videos, depicting typical daily scenarios, and subtle facial and bodily expressions. The videos cover three visual modalities (face, body, Kinect data), and are annotated in terms of emotions (via G-trace) and mood (via the Self-Assessment Manikin and the AffectButton). To annotate the database exhaustively, we exploit crowdsourcing to reach out to an extensive number of nonexpert coders. We validate the reliability of our crowdsourced annotations by (1) adopting a number of criteria to filter out unreliable coders, and (2) comparing the annotations of a subset of our videos with those collected in a controlled lab setting.

Effects of task and image properties on visual-attention deployment in image-quality assessment

Abstract. It is important to understand how humans view images and how their behavior is affected by changes in the properties of the viewed images and the task they are given, particularly the task of scoring the image quality (IQ). This is a complex behavior that holds great importance for the field of image-quality research. This work builds upon 4 years of research work spanning three databases studying image-viewing behavior. Using eye-tracking equipment, it was possible to collect information on human viewing behavior of different kinds of stimuli and under different experimental settings. This work performs a cross-analysis on the results from all these databases using state-of-the-art similarity measures. The results strongly show that asking the viewers to score the IQ significantly changes their viewing behavior. Also muting the color saturation seems to affect the saliency of the images. However, a change in IQ was not consistently found to modify visual attention deployment, neither under free looking nor during scoring. These results are helpful in gaining a better understanding of image viewing behavior under different conditions. They also have important implications on work that collects subjective image-quality scores from human observers.

Relation between the perceived atmosphere of a lit environment and perceptual attributes of light

The impression of a space depends hugely on the light in the space, more specifically on the intensity, colour, beam shape and position of the light sources in that space. This relation though is very complex. The present study aims at understanding the relation between parameters of a lighting design and the resulting perceptions, focusing on the effect that overall brightness and perceived uniformity of the light in the space have on the perceived atmosphere of that space. Employing high-quality visualisations, we found that atmosphere perception can be accurately described by a second-order polynomial as a function of the two perceptual light attributes. In addition, we evaluated how well objective measures reported in literature predict brightness and perceived uniformity.

Design Considerations for Adaptive Lighting to Improve Seniors’ Mood

The advance of LED technologies allows for new design opportunities in the area of lighting for psychological health. Research has shown that lighting in various colors and intensities can be used to improve people’s moods, e.g. through its effects on melatonin levels. This is especially interesting in the context of ambient assisted living and care environments where people are less mobile and spend long hours indoors. The presented work aims at creating a technical system that can detect an older resident’s mood and consequently adapt the lighting in the room to either calm or activate the person. As part of the system’s design process we conducted interviews with caregivers in different care settings (day care, stationary care and home care) to gather requirements for the system. The study provides insights into moods of seniors and their detection, which is formulated in a preliminary mood model, as well as design considerations for different living- and care-settings.

A Comparison of Methodologies to Investigate the Influence of Light on the Atmosphere of a Space

ABSTRACT The impression of a space depends highly on the illumination in the space, which usually is a combination of electric light and daylight. In the present study, we compared three methodologies to study the influence of electric light and daylight on the perception of the light and the perception of the atmosphere of the space. In two experiments, rating scales were used (with a blocked and a random design, respectively) and in a third experiment the paired-comparison method was used to evaluate the light and the atmosphere of the space. In all experiments, visualizations were used to create differently illuminated spaces. All methodologies showed similar effects of daylight and electric light, which attests to the convergent validity of the research methods. However, the methodologies revealed different effect sizes, rendering the paired-comparison design most sensitive to detect the smallest differences. The results also allowed us to explore the contribution of electric light and daylight in creating an atmosphere. The use of visualizations enabled us to control the luminance of daylight and to disentangle the effects of daylight entering a window from the view from a window. The outcomes show that daylight plays a smaller role than electric light on the perception of light and atmosphere in a space when the luminance of daylight is controlled and there is no view outside.

The effect of spatial luminance distribution on dark adaptation

Recent studies show that dark adaptation in the visual system depends on local luminance levels surrounding the viewing direction. These studies, however, do not explain to what extent veiling luminance is responsible for the outcome. To address the latter, in this study dark adaptation was measured for three different spatial luminance distributions surrounding a target to be detected, while keeping the veiling luminance at the location of the target equivalent. The results show that a background with bright areas close to the viewing direction yields longer adaptation times than a background with bright areas at a larger visual angle. Therefore, we conclude that dark adaptation is affected to a great extent by local luminance, even when controlling for veiling luminance. Based on our results, a simple but adequate model is proposed to predict the adaptation luminance threshold for backgrounds having a nonuniform luminance distribution.

The effect of applying 2D enhancement algorithms on 3D video content

Enhancement algorithms are typically applied to video content to increase their appeal to viewers. Such algorithms are readily available in the literature and are already widely applied in, for example, commercially available TVs. On the contrary, not much research has been done on enhancing stereoscopic 3D video content. In this paper, we present research focused on the effect of applying enhancement algorithms used for 2D content on 3D side-by-side content. We evaluate both offline enhancement of video content based on proprietary enhancement algorithms and real-time enhancement in the TVs. This is done using stereoscopic TVs with active shutter glasses, viewed both in their 2D and 3D viewing mode. The results of this research show that 2D enhancement algorithms are a viable first approach to enhance 3D content. In addition to video quality degradation due to the loss of spatial resolution as a consequence of the 3D video format, brightness reduction inherent to polarized or shutter glasses similarly degrades video quality. We illustrate the benefit of providing brightness enhancement for stereoscopic displays.