With the upcoming emergence of the IEEE P3333.1.4 standard, the first ever standardization document on the subjective quality assessment of light field visualization, we are approaching a major milestone of light field Quality of Experience (QoE). The research efforts leading up to this point have answered the fundamental questions regarding perceptual thresholds and personal preference, and best practices regarding research methodologies have been formed. However, in order to introduce successful and efficient light field systems and services, research questions beyond perceptual thresholds and personal preference must be addressed, along with the associated methodologies. In this paper, we propose a comprehensive set of novel research questions and methodologies regarding light field QoE. Our work also provides a detailed discussion of related factors, particularly those that extend to test participants and thus may affect the results of subjective studies.

Three-dimensional visualization technologies such as stereoscopic 3D, virtual reality, and augmented reality have already emerged in training and education; however, light field displays are yet to be introduced in such contexts. In this paper, we characterize light field visualization as a potential candidate for the future of training and education, and compare it to other state-of-the-art 3D technologies. We separately address preschool and elementary school education, middle and high school education, higher education, and specialized training, and assess the suitability of light field displays for these utilization contexts via key performance indicators. This paper exhibits various examples for education, and highlights the differences in terms of display requirements and characteristics. Additionally, our contribution analyzes the scientific-literature-related trends of the past 20 years for 3D technologies, and the past 5 years for the level of education. While the acquired data indicates that light field is still lacking in the context of education, general research on the visualization technology is steadily rising. Finally, we specify a number of future research directions that shall contribute to the emergence of light field visualization for training and education.

Among novel capture and visualization technologies, light field has made significant progress in the current decade, bringing closer its emergence in everyday use cases. Unlike many other forms of 3D displays and devices, light field visualization does not depend on any viewing equipment. Regarding its potential use cases, light field is applicable to both cinematic and interactive contents. Such contents often rely on camera animation, which is a frequent tool for the creation and presentation of 2D contents. However, while common 3D camera animation is often rather straightforward, light field visualization has certain constraints that must be considered before implementing any variation of such techniques. In this paper, we introduce our work on camera animation for light field visualization. Different types of conventional camera animation were applied to light field contents, which produced an interactive simulation. The simulation was visualized and assessed on a real light field display, the results of which are presented and discussed in this paper. Additionally, we tested different forms of realistic physical camera motion in our study, and based on our findings, we propose multiple metrics for the quality evaluation of light field visualization in the investigated context and for the assessment of plausibility.

High Dynamic Range (HDR) imaging has proven its importance in numerous applications over the recent years. In the industry, there is an evident strive to further enhance the quality of the captured contents. Accordingly, legacy Low Dynamic Range (LDR) images are currently being reconstructed as HDR images due to their importance and usage in so many use case contexts. Analogous to conventional LDR and HDR images, the HDR reconstruction of light field images has also become relevant within the scientific community. Although the procedure of reconstruction is similar in several ways, the creation of HDR light field contents poses a significantly greater challenge and suffers from obstacles that are not present in case of the 2D counterpart. In this paper, we provide a context-dependent analysis of HDR light field imaging. The investigated use cases include, but are not limited to industrial prototyping, medical applications, control systems, digital signage, exhibitions of cultural heritage, education, cinematography and communication. The work takes into consideration global illumination and rendering challenges. The topics of real-time systems and services, cost-efficient practices, content availability, baseline-specific considerations, apparatus-specific optical limitations, user interaction and general plausibility are additionally emphasized in the analysis. The paper also provides a set of recommendations regarding the use-case-specific requirements of the investigated practical contexts.

High dynamic range imaging has become a technological trend in the past couple of decades, particularly through its integration into many applications. Numerous attempts were made to reconstruct HDR images from lowdynamic-range data. Such reconstruction techniques can be classified into single-camera and multi-camera approaches. Single-camera setups are less expensive, yet multi-camera setups are more efficient. At the time of this paper, there is already a great number of algorithms for single-camera HDR image reconstruction, but there are only a few for HDR video reconstruction. The latter takes into account the temporal coherence between consecutive video frames, leading to better results. For light field images, this remains a challenging open issue, as the HDR video reconstruction methods do not work as efficiently for light field images as HDR image reconstruction algorithms do. However, analogously to 2D videos, where consecutive frames have temporal coherence, many similarities can be found between the adjacent views of light field contents. In this paper, we investigate the theoretical possibilities of combining CNN architectures utilized for HDR images and videos, in order to enhance the outputs of HDR light field image reconstruction. The concept of our work is to exploit the similarities between light field images since they all visualize the same scene from different angular perspectives.

Among the novel 3D visualization technologies of our era, light field displays provide the complete 3D visual experience without the need for any personal viewing device. Due to the lack of such constraint, these displays may be viewed by any number of observers simultaneously, and the corresponding use case contexts may also involve a virtually unlimited numbers of users; any number that the valid viewing area of the display may accommodate. While many instances of the utilization of this technology operate with static contents, camera animation may also be relevant. While the topic of light field camera animation has already been addressed on an initial level, there are still numerous research efforts to be carried out. In this paper, we elaborate on the lessons learned from implementing light field camera animation. The paper discusses the associated implications, limitations, potentials, and future research efforts. Each of these areas are approached from the perspectives of use cases, visual content, and quality assessment, as well as capture and display hardware. Our work highlights the existing research gaps in the investigated topic, the severe issues related to visualization sharpness, and the lack of appropriate datasets, as well as the constraints due to which novel contents may be captured by virtual cameras instead of real capture systems.