久保 尋之

The decomposition of light transport into direct and global components, diffuse and specular interreflections, and subsurface scattering allows for new visualizations of light in everyday scenes. In particular, indirect light contains a myriad of information about the complex appearance of materials useful for computer vision and inverse rendering applications. In this paper, we present a new imaging technique that captures and analyzes components of indirect light via light transport using a synchronized projector-camera system. The rectified system illuminates the scene with epipolar planes corresponding to projector rows, and we vary two key parameters to capture plane-to-ray light transport between projector row and camera pixel: (1) the offset between projector row and camera row in the rolling shutter (implemented as synchronization delay), and (2) the exposure of the camera row. We describe how this synchronized rolling shutter performs illumination multiplexing, and develop a nonlinear optimization algorithm to demultiplex the resulting 3D light transport operator. Using our system, we are able to capture live short and long-range non-epipolar indirect light transport, disambiguate subsurface scattering, diffuse and specular interreflections, and distinguish materials according to their subsurface scattering properties. In particular, we show the utility of indirect imaging for capturing and analyzing the hidden structure of veins in human skin.

The recent development of 3D printing technology has brought concerns about its potential misuse, such as in copyright infringement, and crimes. Although there have been many studies on blind 3D mesh watermarking for the copyright protection of digital objects, methods applicable to 3D printed objects are rare. In this paper, we propose a novel blind watermarking algorithm for 3D printed objects with applications for copyright protection, traitor tracing, object identification, and crime investigation. Our method allows us to embed a few bits of data into a 3D-printed object, and retrieve it by 3D scanning without requiring any information about the original mesh. The payload is embedded on the object's surface by slightly modifying the distribution of surface norms, that is, the distance between the surface, and the center of gravity. It is robust to resampling and can work with any 3D printer, and scanner technology. In addition, our method increases the capacity, and resistance by subdividing the mesh into a set of bins, and spreading the data over the entire surface to negate the effect of local printing artifacts. The method's novelties include extending the vertex norm histogram to a continuous surface, and the use of 3D moments to synchronize a watermark signal in a 3D-printing context. In the experiments, our method was evaluated using a public dataset against center, orientation, minimum, and maximum norm misalignments; a printing simulation; and actual print/scan experiments using a standard 3D printer, and scanner.

We propose a new blind watermarking algorithm for 3D printed objects that has applications in metadata embedding, robotic grasping, counterfeit prevention, and crime investigation. Our method can be used on fused deposition modeling (FDM) 3D printers and works by modifying the printed layer thickness on small patches of the surface of an object. These patches can be applied to multiple regions of the object, thereby making it resistant to various attacks such as cropping, local deformation, local surface degradation, or printing errors. The novelties of our method are the use of the thickness of printed layers as a one-dimensional carrier signal to embed data, the minimization of distortion by only modifying the layers locally, and one-shot detection using a common paper scanner. To correct encoding or decoding errors, our method combines multiple patches and uses a 2D parity check to estimate the error probability of each bit to obtain a higher correction rate than a naive majority vote. The parity bits included in the patches have a double purpose because, in addition to error detection, they are also used to identify the orientation of the patches. In our experiments, we successfully embedded a watermark into flat surfaces of 3D objects with various filament colors using a standard FDM 3D printer, extracted it using a common 2D paper scanner and evaluated the sensitivity to surface degradation and signal amplitude.

This paper presents a material classification method using an off-the-shelf Time-of-Flight (ToF) camera. The proposed method is built upon a key observation that the depth measurement by a ToF camera is distorted for objects with certain materials, especially with translucent materials. We show that this distortion is due to the variation of time domain impulse responses across materials and also due to the measurement mechanism of the ToF cameras. Specifically, we reveal that the amount of distortion varies according to the modulation frequency of the ToF camera, the object material, and the distance between the camera and object. Our method uses the depth distortion of ToF measurements as a feature for classification and achieves material classification of a scene. Effectiveness of the proposed method is demonstrated by numerical evaluations and real-world experiments, showing its capability of material classification, even for visually indistinguishable objects.

In this research, we propose a novel registration method for three-dimensional (3D) reconstruction from serial section images. 3D reconstructed data from serial section images provides structural information with high resolution. However, there are three problems in 3D reconstruction: non-rigid deformation, tissue discontinuity, and accumulation of scale change. To solve the non-rigid deformation, we propose a novel non-rigid registration method using blending rigid transforms. To avoid the tissue discontinuity, we propose a target image selection method using the criterion based on the blending of transforms. To solve the scale change of tissue, we propose a scale adjustment method using the tissue area before and after registration. The experimental results demonstrate that our method can represent non-rigid deformation with a small number of control points, and is robust to a variation in staining. The results also demonstrate that our target selection method avoids tissue discontinuity and our scale adjustment reduces scale change.

表面下散乱を考慮したレンダリングは，写実的なCGを作成するうえで不可欠である．しかし，表面下散乱を物理的に正しく扱う場合，半透明物体中を進む様々な光の経路を考慮する必要があり，この経路の多さが半透明物体の高速なレンダリングを難しくしている．物体がそれほど透けておらず，多重散乱光が支配的となる材質を仮定したとき，表面下散乱光の寄与は光路が長くなるにつれて急激に小さくなることが知られている．この観察から，半透明物体内部を最短の光学的距離で透過した光ほど，レンダリング結果に対して視覚的により重要であると考えられる．そこで入射光の強度および光学的最短距離の2つを考慮し，最も明るさの寄与が大きくなる表面下散乱光ただ1つを用いて物体表面上の輝度を推定する．本稿ではこれを寄与最大経路と呼び，この経路ただ1つを用いて物体表面上の輝度を推定する．本手法は，寄与最大経路を通った表面下散乱光は視覚的に大きな重要度を持つという経験則に基づく手法である．このような寄与最大経路1 つから表面下散乱光を計算することで，物理的な正しさは保証されないものの，もっともらしいレンダリング結果をリアルタイムに得ることができる．特に，物体内部を考慮した光路の計算コストは非常に高いが，本手法では考慮する経路の本数を限定したことにより，内部に異なる材質の半透明物体が含まれた物体を実時間にレンダリング可能とした．

本研究では，複数のプロジェクタを用いて4次元光線空間を生成する手法を提案し，これにより異なる距離に配置された複数のスクリーンにそれぞれ異なる画像を個別に表示する新たな情報提示方法を実現する．複数のプロジェクタを設置して光線を投射するとき，各スクリーンには異なるプロジェクタから発せられた複数の光線が到達するが，その組み合わせはプロジェクタとスクリーンとの位置関係に応じて異なる．そこで，我々は各スクリーンに表示したい目標画像の輝度勾配を保つことを制約条件にして，各プロジェクタから投影する画像を決定する．これにより，従来法と比較してコントラストを高く保った場合でもアーティファクトの少ない画像を投影可能となる．提案手法の有用性を確かめるためシミュレーション及び実環境実験を行い，その結果を示す．

In this paper, we propose a novel method for animating CG characters that while walking or running pay heed to obstacles. Here, our primary contribution is to formulate a generic visuomotor coordination model for obstacle recognition with whole body movements. In addition, our model easily generates gaze shifts, which expresses the individuality of characters. Based on experimental evidence, we also incorporate the coordination of eye movements in response to obstacle recognition behavior via simple parameters related to the target position and individuality of the characters's gaze shifts. Our overall model can generate plausible visuomotor coordinated movements in various scenes by manipulating parameters of our proposed functions.

写実的なキャラクタアニメーションの実現のためには眼球運動を正しく再現することが重要である．しかしながら現在は，キャラクタの対話時の眼球運動を再現する際にアーティストの手作業による作りこみが必要となるため，多大なコストや労力がかかることが問題である．そこで本研究では人間の対話時の眼球運動に着目し，計測結果を基に眼球運動と瞬きを確率関数を用いてモデル化することで，眼球運動を自動生成する．まず，瞬きを含む対話時の眼球運動と固視微動とをそれぞれ計測する．次に，計測結果を基に対話時の眼球運動を跳躍運動と固視微動に分類する．さらに分類された跳躍運動と固視微動及び瞬きを，それぞれ確率モデルを用いて近似した後に，それらの確率モデルをキャラクタに適用することにより，リアルな眼球運動の自動生成を可能とした．

CGを用いて人間の肌や大理石に代表される半透明物体を表現するために,物体内部で生じる表面下散乱現象を考慮することは有効な手段といえる.しかし表面下散乱の物理的に正確なモデル化には,大域照明モデルを導入せざるを得ず,実時間でのレンダリングにはほど遠いのが現状である.表面下散乱による影響は,物体表面の起伏の激しい点において特に顕著であると考えられる.そこで本研究では物体表面の起伏の強さを表す指標として,曲率を導入する.曲率は物体表面上で局所的に決定されるパラメータであるため,局所照明モデルが適用可能であり,高速なレンダリングが実現される.まず与えられた物体と同じ物質パラメータを有する半径γの球について,単一の白色な平行光源下で球表面の放射輝度分布を推定する.半径rの球面の曲率は1/rで表されるため,様々な半径の球面に対する放射輝度分布を調査することにより,曲率κ,光源と法線とのなす角θ_iに対する反射関数g_r(θ_i,κ)をルックアップテーブル(LUT)として取得する.レンダリング時にはあらかじめ曲率が計算されたポリゴンモデルに対し,LUTをテクスチャとして参照することで,リアルタイムに表面下散乱の影響を考慮したレンダリングが可能となる.