We present a novel method that robustly estimates the reflectance, even in an environment with dynamically changing light. To control the appearance of an object by using a projector-camera system, an appropriate estimate of the object's reflectance is vital to the creation of an appropriate projection image. Most conventional estimation methods assume static light conditions; however, in practice, the appearance is affected by both the reflectance and environmental light. In an environment with dynamically changing light, conventional reflectance estimation methods require calibration every time the conditions change. In contrast, our method requires no additional calibration because it simultaneously estimates both the reflectance and environmental light. Our method is based on the concept of creating two different light conditions by switching the projection at a rate higher than that perceived by the human eye and captures the images of a target object separately under each condition. The reflectance and environmental light are then simultaneously estimated by using the pair of images acquired under these two conditions. We implemented a projector-camera system that switches the projection on and off at 120 Hz. Experiments confirm the robustness of our method when changing the environmental light. Further, our method can robustly estimate the reflectance under practical indoor lighting conditions.

We present computational phase-modulated eyeglasses, a see-through optical system that modulates the view of the user using phase-only spatial light modulators (PSLM). A PSLM is a programmable reflective device that can selectively retardate, or delay, the incoming light rays. As a result, a PSLM works as a computational dynamic lens device. We demonstrate our computational phase-modulated eyeglasses with either a single PSLM or dual PSLMs and show that the concept can realize various optical operations including focus correction, bi-focus, image shift, and field of view manipulation, namely optical zoom. Compared to other programmable optics, computational phase-modulated eyeglasses have the advantage in terms of its versatility. In addition, we also presents some prototypical focus-loop applications where the lens is dynamically optimized based on distances of objects observed by a scene camera. We further discuss the implementation, applications but also discuss limitations of the current prototypes and remaining issues that need to be addressed in future research.

With projection mapping, we can control the appearance of real-world objects by adding illumination. A projector can be used to control light reflected from an object, where the reflected light depends not only on the projection but also on the reflectance and environmental light. Because the resulting colors are affected by the reflectance and environmental light, the presentable color range of a projector is limited. The purpose of this work is to broaden this limited range by focusing on the perceived colors. Although our eyes capture reflected light to perceive the colors of an object, the colors perceived by humans are not always the same as the actual colors, and there are often significant differences between them because of the human visual system. To overcome the limitations of a projector based on human perception, we intentionally generate this difference by inducing a visual illusion, namely, color constancy. In this work, we designed an algorithm to determine the projected colors for presenting the desired colors perceptually by employing a color constancy effect. In addition, we conducted a user study and confirmed that our algorithm can (1) create a misperception regarding the color of illumination, (2) broaden the presentable color range of a projector, and (3) shift the perceptual colors in the desirable direction.

Using projection mapping, we can control the appearance of realworld objects by projecting colored light onto them. Since a projector can only add illumination to the scene, limited color gamut can be presented through projection mapping. However, actual color and perceived color are not always the same, and there is often large difference between them. We intentionally generate this difference by inducing visual illusion for extending the controllable color gamut of a projector. In particular, we induce color constancy. We demonstrate changing object color with and without inducing color constancy. Audiences perceive the controlled colors with and without illusion as different color nevertheless these colors are physically completely same.

In this paper, we propose a method for separating direct and global components of a dynamic scene per illumination color by using a projector-camera system; it exploits both the color switch and the temporal dithering of a DLP projector. Our proposed method is easy-to-implement because it does not require any self-built equipment and temporal synchronization between a projector and a camera. In addition, our method automatically calibrates the projector-camera correspondence in a dynamic scene on the basis of the consistency in pixel intensities, and optimizes the projection pattern on the basis of noise propagation analysis. We implemented the prototype setup and achieved multispectral direct-global separation of dynamic scenes in 60 Hz. Furthermore, we demonstrated that our method is effective for applications such as image-based material editing and multispectral relighting of dynamic scenes where wavelength-dependent phenomena such as fluorescence are observed.

We present a display for optical see-through near-eye displays based on light attenuation, a new paradigm that forms images by spatially subtracting colors of light. Existing optical see-through head-mounted displays (OST-HMDs) form virtual images in an additive manner-they optically combine the light from an embedded light source such as a microdisplay into the users' field of view (FoV). Instead, our light attenuation display filters the color of the real background light pixel-wise in the users' see-through view, resulting in an image as a spatial color filter. Our image formation is complementary to existing light-additive OST-HMDs. The core optical component in our system is a phase-only spatial light modulator (PSLM), a liquid crystal module that can control the phase of the light in each pixel. By combining PSLMs with polarization optics, our system realizes a spatially programmable color filter. In this paper, we introduce our optics design, evaluate the spatial color filter, consider applications including image rendering and FoV color control, and discuss the limitations of the current prototype.

Using projection mapping, we can control the appearance of realworld objects by projecting colored light onto them. Because a projector can only add illumination to the scene, only a limited color gamut can be presented through projection mapping. In this paper we describe how the controllable color gamut can be extended by accounting for human perception and visual illusions. In particular, we induce color constancy to control what color space observers will perceive. In this paper, we explain the concept of our approach, and show first results of our system.

This paper proposes a method for gaze navigation in the real world by projecting an image onto a real object and changing its appearance. In the proposed method, a camera captures an image of objects in the real world. Next all the pixels in the image but those in a specified region are slightly shifted to left and right. Then the obtained image is projected onto the original objects. As a result, the objects not in the specified region looks blurred. We conducted user experiments and showed that the users' gaze were navigated to the specified region.

We present a method for focal distance estimation of a freely-orienting eye using Purkinje-Sanson (PS) images, which are reflections of light on the inner structures of the eye. Using an infrared camera with a rigidly-fixed LED, our method creates an estimation model based on 3D gaze and the distance between reflections in the PS images that occur on the corneal surface and anterior surface of the eye lens. The distance between these two reflections changes with focus, so we associate that information to the focal distance on a user. Unlike conventional methods that mainly relies on 2D pupil size which is sensitive to scene lighting and the fourth PS image, our method detects the third PS image which is more representative of accommodation. Our feasibility study on a single user with a focal range from 15–45 cm shows that our method achieves mean and median absolute errors of 3.15 and 1.93 cm for a 10-degree viewing angle. The study shows that our method is also tolerant against environment lighting changes.

In the field of SAR, the projector-camera system has been well studied; its radiometric model can be easily described by a color mixing matrix. Many SAR applications have proposed and created by using this model. However, this model can be used for reflectance component, but not for fluorescence component. In this paper, we propose RKS Projector-Camera response model for separating of the color mixing matrix's reflectance components and fluorescence components and describe how to decompose them.

We propose a method to calibrate viewpoint-dependent, channel-wise image blur of near-eye displays, especially of Optical See-Through Head-Mounted Displays (OST-HMDs). Imperfections in HMD optics cause channel-wise image shift and blur that degrade the image quality of the display at a user's viewpoint. If we can estimate such characteristics perfectly, we could mitigate the effect by applying correction techniques from the computational photography in computer vision as analogous to cameras. Unfortunately, directly applying existing calibration techniques of cameras to OST-HMDs is not a straightforward task. Unlike ordinary imaging systems, image blur in OST-HMDs is viewpoint-dependent, i.e., the optical characteristic of a display dynamically changes depending on the current viewpoint of the user. This constraint makes the problem challenging since we must measure image blur of an HMD, ideally, over the entire 3D eyebox in which a user can see an image. To overcome this problem, we model the viewpoint-dependent blur as a Gaussian Light Field (GLF) that stores spatial information of the display screen as a (4D) light field with depth information and the blur as point-spread functions in the form of Gaussian kernels, respectively. We first describe both our GLF model and a calibration procedure to learn a GLF for a given OST-HMD. We then apply our calibration method to two HMDs that use different optics: a cubic prism or holographic gratings. The results show that our method achieves significantly better accuracy in Point-Spread Function (PSF) estimations with an accuracy about 2 to 7 dB in Peak SNR.

In this paper, we propose an innovative algorithm for detecting single or multiple ground planes and estimating the orientation of the ground plane with a RGB-D camera. In our algorithm, we use Kernel Density Estimator for selecting the ground plane reliably under a given tilt angle. Camera tilt angle is estimated with probability theory and then used as a feedback to improve the accuracy of detection. Our algorithm is evaluated on several challenging data set and is shown to hold great superiority and effectiveness.

Summary form only given. In this tutorial, we will introduce emerging technologies on computational imaging and light field projection to AR/MR researchers.Light is the most important medium in AR/VR technologies to not only obtain information but also show and modify visual cue in the real scenes. Therefore in this area, latest techniques on optics, imaging and lighting have played an important role to make a next step toward the sophisticated experiences. Computational photography is one of the most influential technology in computer vision and optical engineering areas, and we think most techniques in computational imaging and projection can be applied to common problems in mixed reality, such as scene modeling, modification of the appearances of actual objects and user interactions.

The fundamental issues in Augmented Reality (AR) are on how to naturally mediate the reality with virtual content as seen by users. In AR applications with Optical See-Through Head-Mounted Displays (OST-HMD), the issues often raise the problem of rendering color on the OST-HMD consistently to input colors. However, due to various display constraints and eye properties, it is still a challenging task to indistinguishably reproduce the colors on OST-HMDs. An approach to solve this problem is to pre-process the input color so that a user perceives the output color on the display to be the same as the input. We propose a color calibration method for OST-HMDs. We start from modeling the physical optics in the rendering and perception process between the HMD and the eye. We treat the color distortion as a semi-parametric model which separates the non-linear color distortion and the linear color shift. We demonstrate that calibrated images regain their original appearance on two OST-HMD setups with both synthetic and real datasets. Furthermore, we analyze the limitations of the proposed method and remaining problems of the color reproduction in OST-HMDs. We then discuss how to realize more practical color reproduction methods for future HMD-eye system.

A photomosaic is a type of decorative art made up from various other photographs. We present a method for quickly generating photomosaics and propose an interactive recursive photomosaic system. Users can operate the system by using a large display with a touch input function, which allows them to alter the appearance of the image dynamically.

In this paper, we show that optical inverse tone-mapping (OITM) in light microscopy can improve the visibility of specimens, both when observed directly through the oculars and when imaged with a camera. In contrast to previous microscopy techniques, we premodulate the illumination based on the local modulation properties of the specimen itself. We explain how the modulation of uniform white light by a specimen can be estimated in real time, even though the specimen is continuously but not uniformly illuminated. This information is processed and back-projected constantly, allowing the illumination to be adjusted on the fly if the specimen is moved or the focus or magnification of the microscope is changed. The contrast of the specimen's optical image can be enhanced, and high-intensity highlights can be suppressed. A formal pilot study with users indicates that this optimizes the visibility of spatial structures when observed through the oculars. We also demonstrate that the signal-to-noise (S/N) ratio in digital images of the specimen is higher if captured under an optimized rather than a uniform illumination. In contrast to advanced scanning techniques that maximize the S/N ratio using multiple measurements, our approach is fast because it requires only two images. This can improve image analysis in digital microscopy applications with real-time capturing requirements.

The unified technique for the irradiance correction and appearance enhancement for the real scene is proposed in this paper. The proposed method employed MPC algorithm for the projector camera system and enabled arbitrary appearance control such like photo retouching software in the real world. In the experiment, the appearance control of saturation enhancement, color removal, phase control, edge enhancement, image blur, makes unique brightness and the other enhancements for the real scene are shown.

In this paper, a dynamic appearance enhancement method for the less saturated object is proposed. The appearance enhancement method proposed in this paper is realized with a projector camera dynamic feedback system. Therefore, the proposed method has an ability of the rapid and continuous appearance enhancement and it is useful for the human visual perception assistance. Also, the system not requires a pre-captured appearance of the target.

In this paper, the virtual restoration method of the art piece in the real world is proposed. The correction pattern for restoration is generated from non damaged object's image scanned in advance. As the method to recover the beauty, the marker tracking is used to detect art piece position and the correction image is projected from calibrated LCD projector. In the experiment, the color restoration by a sample image was performed. From the experimental results, the ability of restoration of the discoloring was confirmed in the real world imaginary by the correction image projection.

An application of the pose detection using range images usually uses characteristic matching of the geometrical model but this method has two problems: selecting characteristics from range images is difficult; and it is difficult to make a geometrical model for a complicated shape. Previously a parametric eigen-space method was proposed for pose detection. This method makes object recognition and pose detection possible, but this parametric eigen-space method has a problem that intensity-images depend on a variety of light conditions therefore learning images must include variation of light conditions.