There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

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Flow The Psychology Of Optimal Experience

This paper presents a new reflectance model for rendering computer synthesized images. The model accounts for the relative brightness of different materials and light sources in the same scene. It describes the directional distribution of the reflected light and a color shift that occurs as the reflectance changes with incidence angle. The paper presents a method for obtaining the spectral energy distribution of the light reflected from an object made of a specific real material and discusses a procedure for accurately reproducing the color associated with the spectral energy distribution. The model is applied to the simulation of a metal and a plastic.

A reflectance model for computer graphics

Methods of manufacturing a liquid crystal device including depositing a layer of liquid crystal material on a substrate and imprinting a pattern on the layer of liquid crystal material using an imprint template are disclosed. The liquid crystal material can be jet deposited. The imprint template can include surface relief features, Pancharatnam-Berry Phase Effect (PBPE) structures or diffractive structures. The liquid crystal device manufactured by the methods described herein can be used to manipulate light, such as for beam steering, wavefront shaping, separating wavelengths and/or polarizations, and combining different wavelengths and/or polarizations.

Virtual and augmented reality systems and methods

In this work, we report the set-up and results of the Liver Tumor Segmentation Benchmark (LITS) organized in conjunction with the IEEE International Symposium on Biomedical Imaging (ISBI) 2016 and International Conference On Medical Image Computing Computer Assisted Intervention (MICCAI) 2017. Twenty four valid state-of-the-art liver and liver tumor segmentation algorithms were applied to a set of 131 computed tomography (CT) volumes with different types of tumor contrast levels (hyper-/hypo-intense), abnormalities in tissues (metastasectomie) size and varying amount of lesions. The submitted algorithms have been tested on 70 undisclosed volumes. The dataset is created in collaboration with seven hospitals and research institutions and manually reviewed by independent three radiologists. We found that not a single algorithm performed best for liver and tumors. The best liver segmentation algorithm achieved a Dice score of 0.96(MICCAI) whereas for tumor segmentation the best algorithm evaluated at 0.67(ISBI) and 0.70(MICCAI). The LITS image data and manual annotations continue to be publicly available through an online evaluation system as an ongoing benchmarking resource.

The Liver Tumor Segmentation Benchmark (LiTS)

Foreground-background segmentation is an important problem in computer vision, and it has many applications. We propose a technique of Automatic foreground-background segmentation based on depth from coded aperture. This method first calculates a coarse depth map using technique of coded aperture depth extraction, then estimate the general area of foreground. At last, in order to get the foreground, we use the GrabCut algorithm to segment the image. The entire progress is fully automatic, without any manual intervention. Experiments have proved its effectiveness. And we also did some simple examples for application.

Automatic Foreground-Background Segmentation Based on Depth from Coded Aperture

This paper presents an algorithm based on the ideas of bag of words and sparse representation for action recognition. We assume that all action instances form an action space and all action instances from one action class form a subspace of it. Furthermore, the action space can be represented by an over complete basis and each action instance can be represented by a linear combination of the basis. Naturally, the representation is sparse, so we can solve the problem via l1-minimization. Then the action instance is recognized by how well the basis of one class represents it. Our algorithm is tested on the largest action dataset: KHT dataset. The result shows that our algorithm can work well within a relative small train set.

Sparse representation for action recognition

This paper addresses the identification of large scale outdoor scenes on smart phone by fusing outputs of inertial sensors and computer vision techniques. The main contributions can be summarized as follows: Firstly, we propose an overlap region divide (ORD) method to plot image position area, which is fast enough to find the nearest visiting area and can also reduce the search range compared with the traditional approaches. Secondly, the vocabulary tree based approach is improved by introducing fast geometric consistency constraints (FGCC). Our method involves no operation in the high-dimensional feature space and does not assume a global transform between a pair of images. Thus, it substantially reduces the computational complexity and memory usage, which makes the city scale image recognition feasible on the smartphone. Experiments on a collected database including 0.16 million images show that the proposed method demonstrates excellent identification performance, while maintaining the average identification time of less than 1s.

Outdoor scenes identification on mobile device by integrating vision and inertial sensors

This study proposes an optical-see-through light-field near-eye display (OST LF-NED) based on integral imaging (InI) using a discrete lenslet array (DLA). A light-field image is used as the image source. A special microdisplay array built on a transparent substrate is used as the screen. A DLA is used as a spatial light modulator (SLM) to generate dense light field of the 3-D scene inside the eyebox of the system and provide correct focus cues to the user. The key to realize the OST capacity is that the microdisplays and the lenslets are both discretely-arranged so that the light from the real world passes directly through the gaps among the microdisplays on the transparent substrate and then the flat portion on the DLA panel, providing a clear view of the real world as well as the virtual information. The stray light can be totally eliminated in the region of the eyebox in ideal situations. In practical situations, take the limitation of the F-number into consideration, a trade-off between the size of eyebox and the stray light is made. Analysis and simulation of the stray light are conducted in detail. A ring-shaped aperture on each lenslet is added to reduce the stray light significantly by blocking the screen light that passes by the outer edge of each lenslet. The simulation shows that the proposed method is capable of providing an OST view in LF displays.

Design and stray light analysis of a lenslet-array-based see-through light-field near-eye display

The strive for the small volume and light weight in head-up displays has made the conventional configuration combining relay optics and combiner unpractical any more. In this paper, a compact and light-weight head-up display with a large eyebox is designed, with two orthogonal geometrical waveguides adopted to extend the exit pupil in both directions. This two-dimensional waveguide acts as a pupil expander, which can also save the whole system from the trouble of severe aberrations. A triangular prism serves as the input-coupling and the partially reflective mirrors array is used as the output-coupling. Parameters to shape the combined waveguide are derived. The spherical surface based coaxial projection system to match the combined waveguide are designed to project and magnify the virtual image onto a surface at infinity. The compact head-up display integrating projection optics and the combined waveguide has a horizontal field of 20°, with an eyebox of 80 mmx80 mm.

Yongtian Wang

Papers

Automatic Foreground-Background Segmentation Based on Depth from Coded Aperture

Sparse representation for action recognition

Outdoor scenes identification on mobile device by integrating vision and inertial sensors

Design and stray light analysis of a lenslet-array-based see-through light-field near-eye display

Design of two-dimensional waveguide head-up display