The display coefficients that produce the signal emitted by a light field display are usually calculated to approximate the radiance over a set of sampled rays in the light field space. However, not all information contained in the light field signal is of equal importance to an observer. We propose a retinal pre-filtering of the light field samples that takes into account the image formation process of the observer to determine display coefficients that will ultimately produce better retinal images for a range of focus distances. We demonstrate a significant increase in image definition without changing the display resolution.@en

Purpose: For tumor resection, surgeons need to localize the tumor. For this purpose, a magnetic seed can be inserted into the tumor by a radiologist and, during surgery, a magnetic detection probe informs the distance to the seed for localization. In this case, the surgeon still needs to mentally reconstruct the position of the tumor from the probe’s information. The purpose of this study is to develop and assess a method for 3D localization and visualization of the seed, facilitating the localization of the tumor. Methods: We propose a method for 3D localization of the magnetic seed by extending the magnetic detection probe with a tracking-based localization. We attach a position sensor (QR-code or optical marker) to the probe in order to track its 3D pose (respectively, using a head-mounted display with a camera or optical tracker). Following an acquisition protocol, the 3D probe tip and seed position are subsequently obtained by solving a system of equations based on the distances and the 3D probe poses. Results: The method was evaluated with an optical tracking system. An experimental setup using QR-code tracking (resp. using an optical marker) achieves an average of 1.6 mm (resp. 0.8 mm) 3D distance between the localized seed and the ground truth. Using a breast phantom setup, the average 3D distance is 4.7 mm with a QR-code and 2.1 mm with an optical marker. Conclusion: Tracking the magnetic detection probe allows 3D localization of a magnetic seed, which opens doors for augmented reality target visualization during surgery. Such an approach should enhance the perception of the localized region of interest during the intervention, especially for breast tumor resection where magnetic seeds can already be used in the protocol.

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Disruptive technology has become an integral part of our lives, and it has brought about a significant transformation in the way we interact, communicate, and share information, also in the field of education. Innovation in technology needs to be based on ethics and values of the intended result. As the use of disruptive technology continues to grow, so does the need to understand and consider ethical and value dimensions. How can disruptive technology be developed and used in an ethical way for learning and teaching? What are the values the development and implementation of disruptive technology for education should take into account? How to measure and evaluate values and ethical dimensions of disruptive technology for educational purposes? Are some of the important questions to address. This workshop paper presents a method for eliciting values and ethical dimensions of learning scenarios with disruptive technologies in vocational and higher education settings and illustrates its implementation in the context of the Horizon Europe e-DIPLOMA project. The workshop method, combining value cards and learning scenarios with disruptive technologies, was implemented in seven different countries. The preliminary results of the workshops are presented. The method has the potential to draw peoples’ attention to prospective value concerns and ethical aspects necessary for understanding and acknowledging the consequence of implementing disruptive technologies in education.

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Perspective cues play an important role in painting analysis as it may unveil important characteristics about the painter's techniques and creation process. Nevertheless, extracting perspective lines and their corresponding vanishing points is usually a laborious manual task. Moreover, small variations in the lines may lead to large variations in the vanishing points. In this work, we propose a semi-automatic method to extract perspective lines from paintings in order to mitigate the human variability factor and reduce the workload.@en

Simulating light–matter interaction is a fundamental problem in computer graphics. A particular challenge is the simulation of light interaction with rough surfaces due to diffraction and multiple scattering phenomena. To properly model these phenomena, wave-optics have to be considered. Nevertheless, the most accurate BRDF models, including wave-optics, are computationally expensive, and the resulting renderings have not been systematically compared to real-world measurements. This work sheds more light on reflectance variations due to surface roughness. More specifically, we look at wavelength shifts that lead to reddish and blueish appearances. These wavelength shifts have been scarcely reported in the literature, and, in this paper, we provide the first thorough analysis from precise measured data. We measured the spectral in-plane BRDF of aluminium samples with varying roughness and further acquired the surface topography with a confocal microscope. The measurements show that the rough samples have, on average, a reddish and blueish appearance in the forward and back-scattering, respectively. Our investigations conclude that this is a diffraction-based effect that dominates the overall appearance of the samples. Simulations using a virtual gonioreflectometer further confirm our claims. We propose a linear model that can closely fit such phenomena, where the slope of the wavelength shifts depends on the incident and reflection direction. Based on these insights, we developed a simple BRDF model based on the Cook–Torrance model that considers such wavelength shifts.

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During training sessions, sailors rely on feedback provided by the coaches to reinforce their skills and improve their performance. Nowadays, the incorporation of sensors on the boats enables coaches to potentially provide more informed feedback to the sailors. A common exercise during practice sessions, consists of two boats of the same class, sailing side by side in a straight line with different boat handling techniques. Coaches try to understand which techniques are that make one boat go faster than the other. The analysis of the obtained data from the boats is challenging given its multi-dimensional, time-varying and spatial nature. At present, coaches only rely on aggregated statistics reducing the complexity of the data, hereby losing local and temporal information. We describe a new domain characterization and present a visualization design that allows coaches to analyse the data, structuring their analysis and explore the data from different perspectives. A central element of the tool is the glyph design to intuitively represent and aggregate multiple aspects of the sensor data. We have conducted multiple user studies with naive users, sailors and coaches to evaluate the design and potential of the overall tool. (Figure presented.).

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Video-streaming services usually feature post-processing effects to replace the background. However, these often yield inconsistent lighting. Machine-learning-based relighting methods can address this problem, but, at real-time rates, are restricted to a low resolution and can result in an unrealistic skin appearance. Physically-based rendering techniques require complex skin models that can only be acquired using specialised equipment. Our method is lightweight and uses only a standard smartphone. By correcting imperfections during capture, we extract a convincing physically-based skin model. In combination with suitable acceleration techniques, we achieve real-time rates on commodity hardware.

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Multimodal imaging is used by conservators and scientists to study the composition of paintings. To aid the combined analysis of these digitisations, such images must first be aligned. Rather than proposing a new domain-specific descriptor, we explore and evaluate how existing feature descriptors from related fields can improve the performance of feature-based painting digitisation registration. We benchmark these descriptors on pixel-precise, manually aligned digitisations of ''Girl with a Pearl Earring'' by Johannes Vermeer (c. 1665, Mauritshuis) and of ''18th-Century Portrait of a Woman''. As a baseline we compare against the well-established classical SIFT descriptor. We consider two recent descriptors: the handcrafted multimodal MFD descriptor, and the learned unimodal SuperPoint descriptor. Experiments show that SuperPoint starkly increases description matching accuracy by 40% for modalities with little modality-specific artefacts. Further, performing craquelure segmentation and using the MFD descriptor results in significant description matching accuracy improvements for modalities with many modalityspecific artefacts.@en

Designing realistic tridimensional facial models is a challenging task, not only due to the effort and artistic abilities required but also because human visual perception is very tuned to the processing of facial features. For this reason, rather than creating face models from scratch, artists usually start from a scanned model of a real person. In this work, we present a novel method for blending human faces in order to create a new one. In a nutshell, our proposal uses Laplacian smoothing to segregate layers of details from one or more faces, which are then integrated into a base face with the help of an interactive and visual editor. In particular, our method supports blending multiple faces and multiple sub-regions in those faces. Since our approach is intuitive and relatively easy to implement, it can be integrated into artistic pipelines aiming at designing human face models from preexisting ones.

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Craniotomy is a procedure where neurosurgeons open the patient’s skull to gain direct access to the brain. The craniotomy’s position defines the access path from the skull surface to the tumour and, consequently, the healthy brain tissue to be removed to reach the tumour. This is a complex procedure where a neurosurgeon is required to mentally reconstruct spatial relations of important brain structures to avoid removing them as much as possible. We propose a visualisation method using Augmented Reality to assist in the planning of a craniotomy. The goal of this study is to visualise important brain structures aligned with the physical position of the patient and to allow a better perception of the spatial relations of the structures. Additionally, a heat map was developed that is projected on top of the skull to provide a quick overview of the structures between a chosen location on the skull and the tumour. In the experiments, tracking accuracy was assessed, and colour maps were assessed for use in an AR device. Additionally, we conducted a user study amongst neurosurgeons and surgeons from other fields to evaluate the proposed visualisation using a phantom head. Most participants indeed agree that the visualisation can assist in planning a craniotomy and feedback on future improvements towards the clinical scenario was collected. (see https://www.acm.org/publications/class-2012)

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One common way to aid coaching and seek to improve athletes’ performance is by recording training sessions for posterior analysis. In the case of sailing, coaches record videos from another boat, but usually rely on handheld devices, which may lead to issues with the footage and missing important moments. On the other hand, by autonomously recording the entire session with a fixed camera, the analysis becomes challenging owing to the length of the video and possible stabilization issues. In this work, we aim to facilitate the analysis of such full-session videos by automatically extracting maneuvers and providing a visualization framework to readily locate interesting moments. Moreover, we address issues related to image stability. Finally, an evaluation of the framework points to the benefits of video stabilization in this scenario and an appropriate accuracy of the maneuver detection method.@en

We present a method to recover the 3D flying shape of a sail using passive markers. In the navigation and naval architecture domain, retrieving the sail shape may be of immense value to confirm or contest simulation results, and to aid the design of new optimal sails. Our acquisition setup is very simple and low-cost, as it is only necessary to fix a series of printable markers on the sail and register the flying shape in real sailing conditions from a side vessel with a single camera. We reconstruct the average sail shape during an interval where the sailor maintains the sail as stable as possible. The average is further improved by a Bundle Adjustment algorithm. We tested our method in a real sailing scenario and present promising results. Quantitatively, we show the precision in regards to the reconstructed markers area and the reprojected points. Qualitatively, we present feedback from domain experts who evaluated our results and confirmed the usefulness and quality of the reconstructed shape.

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While sailing, sailors rely on their eyes to inspect the sail shape and adjust the configurations to achieve an appropriate shape for a certain the weather condition. Mastering this so-called trimming process requires years of experience since the visual inspection of the sail shape suffers from inaccuracies and many times are difficult to communicate verbally. Therefore, this research proposes a visual analysis tool that presents an accurate sail shape representation and supports sailors in investigating the optimal sail shape for certain weather conditions. In order to achieve our goals, we reconstruct the 3D sail shape from point clouds acquired by photogrammetry methods. For incomplete acquisitions we deform a complete template sail to estimate the missing parts. We designed a visualization dashboard for sailors to explore the 3D structure, 2D profiles and characteristics of the time-varying sail shape as well as analyze their relation to boat speed. The usability of the visualization tool is tested through a qualitative evaluation with two sailing experts. The result shows that the reconstruction and deformation of sail shape are plausible. Furthermore, the visualization dashboard has the potential to enhance sailors’ comprehension of sail shape and provide insights towards optimal trimming. @en

Nowadays video plays an important role in the coaching of athletes across many different sports. For sailing training sessions, the videos are recorded from the coach boat and provide ways to review and analyze the training sessions aiming at improving the sailors performance. On one hand, videos are commonly recorded with handheld devices that are rather cumbersome to acquire and are prone to missing many important moments. On the other hand, recordings of entire sessions with an integrated camera in the coach boat are difficult to analyze given their length and the lack of image stability. We present a pipeline to facilitate the visual analysis of these full session videos. We extract manoeuvres as interesting segments, and provide a visualization framework to present the video and processed data. Manoeuvres are extracted by detecting and tracking the boat and sailors. With the visualization tool, the user can locate and visually inspect those manoeuvres for coaching tasks. We evaluated the potential of the framework and from the results we conclude that the manoeuvre detection is reasonably accurate and some coaches see potential in the presented framework.@en

The simulation of light-matter interaction is a major challenge in computer graphics. Particularly challenging is the modelling of light-matter interaction of rough surfaces, which contain several different scales of roughness where many different scattering phenomena take place. There are still appearance critical phenomena that are weakly approximated or even not included at all by current BRDF models. One of these phenomena is the reddening effect, which describes a tilting of the reflectance spectra towards long wavelengths especially in the specular reflection. The observation that the reddening effect takes place on rough surfaces is new and the characteristics and source of the reddening effect have not been thoroughly researched and explained. Furthermore, it was not even clear whether the reddening really exists or the observed effect resulted from measurement errors. In this work we give a short introduction to the reddening effect and show that it is indeed a property of the material reflectance function, and does not originate from measurement errors or optical aberrations.@en

Rendering large point clouds ordinarily requires building a hierarchical data structure for accessing the points that best represent the object for a given viewing frustum and level-of-detail. The building of such data structures frequently represents a large portion of the cost of the rendering pipeline both in terms of time and space complexity, especially when rendering is done for inspection purposes only. This problem has been addressed in the past by incremental construction approaches, but these either result in low quality hierarchies or in longer construction times. In this work we present OMiCroN – Oblique Multipass Hierarchy Creation while Navigating – which is the first algorithm capable of immediately displaying partial renders of the geometry, provided the cloud is made available sorted in Morton order. OMiCroN is fast, being capable of building the entire data structure in memory spending an amount of time that is comparable to that of just reading the cloud from disk. Thus, there is no need for storing an expensive hierarchy, nor for delaying the rendering until the whole hierarchy is read from disk. In fact, a pipeline coupling OMiCroN with an incremental sorting algorithm running in parallel can start rendering as soon as the first sorted prefix is produced, making this setup very convenient for streamed viewing.

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Shadow volumes are a popular technique to compute pixel-accurate hard shadows in 3D scenes. Many variants exist that trade off accuracy and efficiency. In this work, we present an artifact-free, efficient, and easy-to-implement stencil shadow volume method. We compare our method to established stencil shadow volume techniques and show that it outperforms the alternatives.

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