Fast Correction of Tiled Display Systems on Planar Surfaces

A method for fast colour and geometric correction of a tiled display system is presented in this paper. Such kind of displays are a common choice for virtual reality applications and simulators, where a high resolution image is required. They are the cheapest and more flexible alternative for large image generation but they require a precise geometric and colour correction. The purpose of the proposed method is to correct the projection system as fast as possible so in case the system needs to be recalibrated it doesn’t interfere with the normal operation of the simulator or virtual reality application. This technique makes use of a single conventional webcam for both geometric and photometric correction. Some previous assumptions are made, like planar projection surface and negligibleintra-projector colour variation and black-offset levels. If these assumptions hold true, geometric and photometric seamlessness can be achievedfor this kind of display systems. The method described in this paper is scalable for an undefined number of projectors and completely automatic

INFORMATION TECHNOLOGY FOR NEXT-GENERATION OF SURGICAL ENVIRONMENTS

Minimally invasive surgeries (MIS) are fundamentally constrained by image quality,access to the operative field, and the visualization environment on which thesurgeon relies for real-time information. Although invasive access benefits the patient,it also leads to more challenging procedures, which require better skills andtraining. Endoscopic surgeries rely heavily on 2D interfaces, introducing additionalchallenges due to the loss of depth perception, the lack of 3-Dimensional imaging,and the reduction of degrees of freedom.By using state-of-the-art technology within a distributed computational architecture,it is possible to incorporate multiple sensors, hybrid display devices, and3D visualization algorithms within a exible surgical environment. Such environmentscan assist the surgeon with valuable information that goes far beyond what iscurrently available. In this thesis, we will discuss how 3D visualization and reconstruction,stereo displays, high-resolution display devices, and tracking techniques arekey elements in the next-generation of surgical environments

CompenNet++: End-to-end Full Projector Compensation

Full projector compensation aims to modify a projector input image such that it can compensate for both geometric and photometric disturbance of the projection surface. Traditional methods usually solve the two parts separately, although they are known to correlate with each other. In this paper, we propose the first end-to-end solution, named CompenNet++, to solve the two problems jointly. Our work non-trivially extends CompenNet, which was recently proposed for photometric compensation with promising performance. First, we propose a novel geometric correction subnet, which is designed with a cascaded coarse-to-fine structure to learn the sampling grid directly from photometric sampling images. Second, by concatenating the geometric correction subset with CompenNet, CompenNet++ accomplishes full projector compensation and is end-to-end trainable. Third, after training, we significantly simplify both geometric and photometric compensation parts, and hence largely improves the running time efficiency. Moreover, we construct the first setup-independent full compensation benchmark to facilitate the study on this topic. In our thorough experiments, our method shows clear advantages over previous arts with promising compensation quality and meanwhile being practically convenient.Comment: To appear in ICCV 2019. High-res supplementary material: https://www3.cs.stonybrook.edu/~hling/publication/CompenNet++_sup-high-res.pdf. Code: https://github.com/BingyaoHuang/CompenNet-plusplu

A Multi-Projector Calibration Method for Virtual Reality Simulators with Analytically Defined Screens

The geometric calibration of projectors is a demanding task, particularly for the industry of virtual reality simulators. Different methods have been developed during the last decades to retrieve the intrinsic and extrinsic parameters of projectors, most of them being based on planar homographies and some requiring an extended calibration process. The aim of our research work is to design a fast and user-friendly method to provide multi-projector calibration on analytically defined screens, where a sample is shown for a virtual reality Formula 1 simulator that has a cylindrical screen. The proposed method results from the combination of surveying, photogrammetry and image processing approaches, and has been designed by considering the spatial restrictions of virtual reality simulators. The method has been validated from a mathematical point of view, and the complete system which is currently installed in a shopping mall in Spain has been tested by different users

Laser Pointer Tracking in Projector-Augmented Architectural Environments

We present a system that applies a custom-built pan-tilt-zoom camera for laser-pointer tracking in arbitrary real environments. Once placed in a building environment, it carries out a fully automatic self-registration, registrations of projectors, and sampling of surface parameters, such as geometry and reflectivity. After these steps, it can be used for tracking a laser spot on the surface as well as an LED marker in 3D space, using inter-playing fisheye context and controllable detail cameras. The captured surface information can be used for masking out areas that are critical to laser-pointer tracking, and for guiding geometric and radiometric image correction techniques that enable a projector-based augmentation on arbitrary surfaces. We describe a distributed software framework that couples laser-pointer tracking for interaction, projector-based AR as well as video see-through AR for visualizations with the domain specific functionality of existing desktop tools for architectural planning, simulation and building surveying

Laser Pointer Tracking in Projector-Augmented Architectural Environments

We present a system that applies a custom-built pan-tilt-zoom camera for laser-pointer tracking in arbitrary real environments. Once placed in a building environment, it carries out a fully automatic self-registration, registrations of projectors, and sampling of surface parameters, such as geometry and reflectivity. After these steps, it can be used for tracking a laser spot on the surface as well as an LED marker in 3D space, using inter-playing fisheye context and controllable detail cameras. The captured surface information can be used for masking out areas that are critical to laser-pointer tracking, and for guiding geometric and radiometric image correction techniques that enable a projector-based augmentation on arbitrary surfaces. We describe a distributed software framework that couples laser-pointer tracking for interaction, projector-based AR as well as video see-through AR for visualizations with the domain specific functionality of existing desktop tools for architectural planning, simulation and building surveying

Camera based Display Image Quality Assessment

This thesis presents the outcomes of research carried out by the PhD candidate Ping Zhao during 2012 to 2015 in Gjøvik University College. The underlying research was a part of the HyPerCept project, in the program of Strategic Projects for University Colleges, which was funded by The Research Council of Norway. The research was engaged under the supervision of Professor Jon Yngve Hardeberg and co-supervision of Associate Professor Marius Pedersen, from The Norwegian Colour and Visual Computing Laboratory, in the Faculty of Computer Science and Media Technology of Gjøvik University College; as well as the co-supervision of Associate Professor Jean-Baptiste Thomas, from The Laboratoire Electronique, Informatique et Image, in the Faculty of Computer Science of Universit´e de Bourgogne. The main goal of this research was to develop a fast and an inexpensive camera based display image quality assessment framework. Due to the limited time frame, we decided to focus only on projection displays with static images displayed on them. However, the proposed methods were not limited to projection displays, and they were expected to work with other types of displays, such as desktop monitors, laptop screens, smart phone screens, etc., with limited modifications. The primary contributions from this research can be summarized as follows: 1. We proposed a camera based display image quality assessment framework, which was originally designed for projection displays but it can be used for other types of displays with limited modifications. 2. We proposed a method to calibrate the camera in order to eliminate unwanted vignetting artifact, which is mainly introduced by the camera lens. 3. We proposed a method to optimize the camera’s exposure with respect to the measured luminance of incident light, so that after the calibration all camera sensors share a common linear response region. 4. We proposed a marker-less and view-independent method to register one captured image with its original at a sub-pixel level, so that we can incorporate existing full reference image quality metrics without modifying them. 5. We identified spatial uniformity, contrast and sharpness as the most important image quality attributes for projection displays, and we used the proposed framework to evaluate the prediction performance of the state-of-the-art image quality metrics regarding these attributes. The proposed image quality assessment framework is the core contribution of this research. Comparing to conventional image quality assessment approaches, which were largely based on the measurements of colorimeter or spectroradiometer, using camera as the acquisition device has the advantages of quickly recording all displayed pixels in one shot, relatively inexpensive to purchase the instrument. Therefore, the consumption of time and resources for image quality assessment can be largely reduced. We proposed a method to calibrate the camera in order to eliminate unwanted vignetting artifact primarily introduced by the camera lens. We used a hazy sky as a closely uniform light source, and the vignetting mask was generated with respect to the median sensor responses over i only a few rotated shots of the same spot on the sky. We also proposed a method to quickly determine whether all camera sensors were sharing a common linear response region. In order to incorporate existing full reference image quality metrics without modifying them, an accurate registration of pairs of pixels between one captured image and its original is required. We proposed a marker-less and view-independent image registration method to solve this problem. The experimental results proved that the proposed method worked well in the viewing conditions with a low ambient light. We further identified spatial uniformity, contrast and sharpness as the most important image quality attributes for projection displays. Subsequently, we used the developed framework to objectively evaluate the prediction performance of the state-of-art image quality metrics regarding these attributes in a robust manner. In this process, the metrics were benchmarked with respect to the correlations between the prediction results and the perceptual ratings collected from subjective experiments. The analysis of the experimental results indicated that our proposed methods were effective and efficient. Subjective experiment is an essential component for image quality assessment; however it can be time and resource consuming, especially in the cases that additional image distortion levels are required to extend the existing subjective experimental results. For this reason, we investigated the possibility of extending subjective experiments with baseline adjustment method, and we found that the method could work well if appropriate strategies were applied. The underlying strategies referred to the best distortion levels to be included in the baseline, as well as the number of them