One step closer to a better experience: analysis of the suitable viewing distance ranges of light field visualization usage contexts for observers with reduced visual capabilities

Abstract

Light field visualization technology offers a glasses-free 3D experience that may be enjoyed by multiple observers simultaneously. The overall visual experience depends on a multitude of factors, among which is light ray density. In case of horizontal-only parallax displays, it defines the smoothness of the horizontal motion parallax, which is crucial to visualization quality. However, the perceived light ray density naturally depends on the viewing distance; the farther the observer is, the fewer light rays may address the two pupils, with respect to a single point on the screen. Research on this topic has already been initiated and the first results are now available in the scientific literature. However, the experiment, similarly to the vast majority of research efforts regarding the perceived quality of light field visualization, is built on the participation of individuals that are screened for normal vision. Yet a notable portion of potential future users would not pass such screening, particularly the Snellen chart on visual acuity. In this paper, we investigate the suitability of viewing distances for the future use cases of light field visualization from the perspective of users with reduced visual capabilities. The subjective tests evaluate contexts of passive visual consumption, such as a cinematic experience or an exhibition of cultural heritage. The selected use cases are not only assessed by their natural viewing distance intervals, but by closer and farther distances as well. The output of the research aims to extend the social inclusion of potential systems and services of light field visualization.

Light Field Visualization for Training and Education: A Review

“…However, note that fully synthetic contents do not necessitate high spatial resolution [99,100]. Additionally, resolution values may impact students with reduced visual capabilities differently, fundamentally depending on the viewing distance [101].…”

“…Regarding visually impaired students, a study was conducted to investigate their psycho-physiological problems, the results of which indicate positive correlations between visual impairments and psychological effects [127]. Visual impairments may have a fundamental impact on the perceived quality of LF visualization-as emphasized by the results of Simon et al [101]-and thus may pose significant challenges regarding the effectiveness of educational use cases.…”

How I Met Your V2X Sensor Data: Analysis of Projection-Based Light Field Visualization for Vehicle-to-Everything Communication Protocols and Use Cases

“…Recent works on light field technology cover the topics of angular enhancement [ 100 , 101 , 102 ] (which aims to achieve super-resolution), image enhancement [ 103 , 104 , 105 ] (which is also often named super-resolution, and thus, the terminology of the other one is becoming “angular super-resolution”), saliency detection [ 106 , 107 , 108 ], light field rendering [ 109 , 110 , 111 ] and reconstruction [ 112 , 113 , 114 ], microscopy [ 115 , 116 , 117 ], camera animation [ 118 ], video streaming [ 119 ], objective quality assessment [ 120 , 121 ], perceived quality [ 94 , 122 ], and many more. Every single experiment that studies the projection-based light field visualization with the involvement of human individuals is summarized in a recent work [ 123 ], along with a thorough analysis of future research efforts, and an up-to-date survey [ 124 ] investigates the associated methods.…”

The Good News, the Bad News, and the Ugly Truth: A Review on the 3D Interaction of Light Field Displays

“…In the context of light field visualization, subjective quality evaluation commonly accompanies research efforts related to compression [81][82][83][84][85][86][87][88]. Other topics addressing light field QoE include, but are definitely not limited to, objective quality assessment (i.e., the prediction or estimation of subjectively perceived quality through metrics and models) [89][90][91][92][93][94]; datasets for objective and subjective assessment [95][96][97][98][99][100][101][102][103]; reconstruction, subsampling, interpolation, and view synthesis [104][105][106][107][108][109][110]; spatial and angular resolution [111][112][113][114]; methodology and viewing conditions [115][116][117][118][119][120]; human factors and content impact [121][122][123][124]; and rendering [125]…”