軸はずし投影による視点依存立体画像の半球面への投影法の検討

　この研究は、テーブルトップの知覚空間を半球面スクリーンによって拡張することを目的とする。通常、ユーザに混合現実感を与えるためには、ヘッドマウントディスプレイや、デバイス上の実空間画像への情報表示が一般的に行われる。それらに対し、この半球面ディスプレイは、自然なユーザインタフェースを提供できる。これまでに筆者は、運動視差による立体認知が可能なシステムを提案してきた[3][6][7]。このシステムは、安価で手軽なデバイスによって実現可能であるが、スクリーンの位置は光軸中心に固定されていた。今回の発表では、このスクリーン位置を自由に変更できるよう、光軸から外れた斜め方向からの投影による画像変換手法を提案する。また同時に、厳密な画像変換手法の計算量を軽減するために、近似計算手法を提案・評価し、リアルタイムなインタラクションの実現に向けた実装を行った。In this paper, I introduce an application to expand a tabletop with a hemisphere screen. In the terms of mixed reality (MR), two methods are commonly used. One is to utilize a device such as HMD to show information within the users\u27 view. ARToolKit[2] is one of the most powerful tools to create such kind of applications. The other is to show a real camera view with virtual information onto a display. Spherical/hemispherical screens that can expand the tabletop are proposed.[3][6] Spherical screen has better sense of immersion compared to a flat display. A hemisphere screen system is proposed to show volumetric perception space to the user with motion parallax.[7] The component of the system is simple and easy to confirm, though the projection ray must come right vertically to the table plane. I have improved the projection method to enable off-axis diagonal projection. The diagonal projection reduces the restriction to the position of the projector. Additionally, the approximated method to simplify the transformation is discussed for the real-time rendering to enable the movement of the screen. The system has possibility to be expanded to track display position and users view point to give more immersive impression on their tabletop

Painting Lighting and Viewing Effects

We present a system for painting how the appearance of an object changes under different lighting and viewing conditions. The user paints what the object should look like under different lighting conditions (dark, partially dark, fully lit, etc.) and (optionally) different viewing angles. The system renders the object under new lighting conditions and a new viewing angle by combining these paintings. We also provide a technique for constructing texture maps directly from the user’s paintings

Omnidirectional texturing of human actors from multiple view video sequences

International audienceIn 3D video, recorded object behaviors can be observed from any viewpoint, because the 3D video registers the object's 3D shape and color. However, the real-world views are limited to the views from a number of cameras, so only a coarse model of the object can be recovered in real-time. It becomes then necessary to judiciously texture the object with images recovered from the cameras. One of the problems in multi-texturing is to decide what portion of the 3D model is visible from what camera. We propose a texture-mapping algorithm that tries to bypass the problem of exactly deciding if a point is visible or not from a certain camera. Given more than two color values for each pixel, a statistical test allows to exclude outlying color data before blending

GPU-Based Optimization of a Free-Viewpoint Video System

We present a method for optimizing the reconstruction and rendering of 3D objects from multiple images by utilizing the latest features of consumer-level graphics hardware based on shader model 4.0. We accelerate visual hull reconstruction by rewriting a shape-from-silhouette algorithm to execute on the GPU's parallel architecture. Rendering a is optimized through the application of geometry shaders to generate billboarding microfacets textured with captured images. We also present a method for handling occlusion in the camera selection process that is optimized for execution on the GPU. Execution time is further improved by rendering intermediate results directly to texture to minimize the number of data transfers between graphics and main memory. We show our GPU based system to be significantly more efficient than a purely CPU-based approach, due to the parallel nature of the GPU, while maintaining graphical quality

Moving object detection from a point cloud using photometric and depth consistencies

ICPR 2016: 23rd International Conference on Pattern Recognition, Dec 4-8, 2016, Cancun, Mexico3D models of outdoor environments have been used for several applications such as a virtual earth system and a vision-based vehicle safety system. 3D data for constructing such 3D models are often measured by an on-vehicle system equipped with laser rangefinders, cameras, and GPS/IMU. However, 3D data of moving objects on streets lead to inaccurate 3D models when modeling outdoor environments. To solve this problem, this paper proposes a moving object detection method for point clouds by minimizing an energy function based on photometric and depth consistencies assuming that input data consist of synchronized point clouds, images, and camera poses from a single sequence captured with a moving on-vehicle system

Seamless, Static Multi-Texturing of 3D Meshes

In the context of 3D reconstruction, we present a static multi-texturing system yielding a seamless texture atlas calculated by combining the colour information from several photos from the same subject covering most of its surface. These pictures can be provided by shooting just one camera several times when reconstructing a static object, or a set of synchronized cameras, when dealing with a human or any other moving object. We suppress the colour seams due to image misalignments and irregular lighting conditions that multi-texturing approaches typically suffer from, while minimizing the blurring effect introduced by colour blending techniques. Our system is robust enough to compensate for the almost inevitable inaccuracies of 3D meshes obtained with visual hull–based techniques: errors in silhouette segmentation, inherently bad handling of concavities, etc