We propose a method of extracting watermark from 3D prints created from 3D mesh data. The watermark is embedded to the 3D mesh in the spectral domain using a robust, imperceptible, and informed algorithm based on the spread spectrum technique, and then extracted from 3D prints by reconstructing the 3D mesh homologous to the original. A suspect 3D mesh is reconstructed accurately and robustly from noisy and incomplete 3D scans of the 3D prints, by optimizing a sparse subset of the spectrum using a variant of the iterative closest point technique. The mesh is registered to the original mesh by construction, in terms of geometry and topology, which allows us to extract a suspect watermark by simple algebraic operations. Comprehensive experiments have been conducted to demonstrate the performance of our method using standard 3D datasets and multiple 3D printers. The proposed method significantly outperforms prior methods under different conditions in the practical scenario. The probability of false positive detection is kept less than 106 for the most cases of simulated and real data.

We present a method of modeling the three-dimensional shape of a deforming object from a time-series of range images. A non-rigid variant of ICP algorithm is proposed to solve the correspondence between the range images. The deformation is modeled by the combination of piecewise similarity transformation using differential coordinates, and solved stably and efficiently by alternating minimization of a quadratic objective function. The performance of the proposed method is demonstrated by conducting two modeling tasks. First, the complete shapes of human hand and full-body are reconstructed by integrating the range images acquired by a single depth camera. Second, the shape completion of four-dimensional scan data is carried out by fitting a template model to the point clouds by extending our registration technique in the spatiotemporal domain.

This paper proposes a new methodology for synthesizing animations of multiple characters, allowing them to intelligently compete with one another in dense environments, while still satisfying requirements set by an animator. To achieve these two conflicting objectives simultaneously, our method separately evaluates the competition and collaboration of the interactions, integrating the scores to select an action that maximizes both criteria. We extend the idea of min-max search, normally used for strategic games such as chess. Using our method, animators can efficiently produce scenes of dense character interactions such as those in collective sports or martial arts. The method is especially effective for producing animations along story lines, where the characters must follow multiple objectives, while still accommodating geometric and kinematic constraints from the environment.

We propose a novel color code, Hamming color code, designed for rapid 3D shape acquisition using structured light projection. The Hamming color code has several properties which are desirable for practical 3D acquisition as follows. First, the Hamming distance of adjacent colors is always 1, which makes the color detection robust to color blending due to defocusing, subsurface scattering, or chromatic aberration. Second, the substrings of a certain length is guaranteed to be unique. In other words, the Hamming code can be viewed as a subset of de Bruijn sequence. Third, a one-dimensional coordinate can be encoded for each pixel, which enables dense 3D reconstruction from a single pattern projection. Thanks to the uniqueness and robustness of the substrings, the structured light can be decoded stably by dynamic programming. We have implemented parallel dynamic programming on GPU and achieved the speed-up by a factor of 630 compared to the CPU-based implementation, and accomplished video-rate 3D acquisition using commodity hardware. Several experiments have been conducted to demonstrate the stability and performance of our algorithm. Finally we discuss the limitation and future direction of this work.

Efficient computation of strategic movements is essential to control virtual avatars intelligently in computer games and 3D virtual environments. Such a module is needed to control non-player characters (NPCs) to fight, play team sports or move through a mass crowd. Reinforcement learning is an approach to achieve real-time optimal control. However, the huge state space of human interactions makes it difficult to apply existing learning methods to control avatars when they have dense interactions with other characters. In this research, we propose a new methodology to efficiently plan the movements of an avatar interacting with another. We make use of the fact that the subspace of meaningful interactions is much smaller than the whole state space of two avatars. We efficiently collect samples by exploring the subspace where dense interactions between the avatars occur and favor samples that have high connectivity with the other samples. Using the collected samples, a finite state machine (FSM) called Interaction Graph is composed. At run-time, we compute the optimal action of each avatar by minmax search or dynamic programming on the Interaction Graph. The methodology is applicable to control NPCs in fighting and ball-sports games.

We propose a data-driven approach to automatically generate a scene where tens to hundreds of characters densely interact with each other. During off-line processing, the close interactions between characters are precomputed by expanding a game tree, and these are stored as data structures called interaction patches. Then, during run-time, the system spatio-temporally concatenates the interaction patches to create scenes where a large number of characters closely interact with one another. Using our method, it is possible to automatically or interactively produce animations of crowds interacting with each other in a stylized way. The method can be used for a variety of applications including TV programs, advertisements and movies.

Acquiring 3D models of intricate objects (like tree branches, bicycles and insects) is a hard problem due to severe self-occlusions, repeated thin structures and surface discontinuities. In theory, a shape-from-silhouettes (SFS) approach can overcome these difficulties and use many views to reconstruct visual hulls that are close to the actual shapes. In practice, however, SFS is highly sensitive to errors in silhouette contours and the calibration of the imaging system, and therefore not suitable for obtaining reliable shapes with a large number of views. We present a practical approach to SFS using a novel technique called coplanar shadowgram imaging, that allows us to use dozens to even hundreds of views for visual hull reconstruction. Here, a point light source is moved around an object and the shadows (silhouettes) cast onto a single background plane are observed. We characterize this imaging system in terms of image projection, reconstruction ambiguity, epipolar geometry, and shape and source recovery. The coplanarity of the shadowgrams yields novel geometric properties that are not possible in traditional multi-view camera- based imaging systems. These properties allow us to derive a robust and automatic algorithm to recover the visual hull of an object and the 3D positions of light source simultaneously, regardless of the complexity of the object. We demonstrate the acquisition of several intricate shapes with severe occlusions and thin structures, using 50 to 120 views.

It is difficult to create scenes where multiple avatars are fighting / competing with each other. Manually creating the motions of avatars is time consuming due to the correlation of the movements between the avatars. Capturing the motions of multiple avatars is also difficult as it requires a huge amount of post-processing. In this paper, we propose a new method to generate a realistic scene of avatars densely interacting in a competitive environment. The motions of the avatars are considered to be captured individually, which will increase the easiness of obtaining the data. We propose a new algorithm called the temporal expansion approach which maps the continuous time action plan to a discrete space such that turn-based evaluation methods can be used. As a result, many mature algorithms in game such as the min-max search and α---β pruning can be applied. Using our method, avatars will plan their strategies taking into account the reaction of the opponent. Fighting scenes with multiple avatars are generated to demonstrate the effectiveness of our algorithm. The proposed method can also be applied to other kinds of continuous activities that require strategy planning such as sport games.

This paper presents a method for automatic determination of dense and smooth mapping between two images without a priori knowledge of either the camera pose or the objects in the images. We designed an algorithm to find the mapping between a pair of arbitrary images, and accomplish automatic image morphing. In order to extract image features which look natural to human, we use a set of linear filters similar to those that are used in early vision. Then the derived vector fields consisting of filter responses are matched with each other through a minimization of the cost function which expresses the similarity of transformed images and mapping smoothness, in a multiresolutional hierarchy. Since the cost function in general is highly nonlinear, we avoid excessive distortion in the estimated mapping by providing a local convexity of mapping in nonlinear optimization. In this paper, a variety of experimental results are discussed for various data sets, including images of rotating objects, static objects, human faces and texture patterns, to demonstrate the performance of the proposed method.

In this article, we present an image-based modeling and rendering system, which we call pop-up light field , that models a sparse light field using a set of coherent layers . In our system, the user specifies how many coherent layers should be modeled or popped up according to the scene complexity. A coherent layer is defined as a collection of corresponding planar regions in the light field images. A coherent layer can be rendered free of aliasing all by itself, or against other background layers. To construct coherent layers, we introduce a Bayesian approach, coherence matting , to estimate alpha matting around segmented layer boundaries by incorporating a coherence prior in order to maintain coherence across images.We have developed an intuitive and easy-to-use user interface (UI) to facilitate pop-up light field construction. The key to our UI is the concept of human-in-the-loop where the user specifies where aliasing occurs in the rendered image. The user input is reflected in the input light field images where pop-up layers can be modified. The user feedback is instant through a hardware-accelerated real-time pop-up light field renderer. Experimental results demonstrate that our system is capable of rendering anti-aliased novel views from a sparse light field.

We present a method of visualizing volume-sampled distance fields, taking advantage of hardware-acceleration of modern graphics hardware. Although conventional distance fields can represent only 2-manifold surfaces in a stable way, we have developed a technique of representing both manifold and non-manifold surfaces in a volume created by sampling a segmented distance field. The volume-sampled distance fields can be visualized effectively with pre-integrated volume rendering by embedding the interpolating function as a lookup table called vertex generation diagram into graphics hardware. We developed a simple system for smoothly blending two surface models in the distance function domain, and confirmed that our proposed representation of surface models is applicable to existing methods of geometric processing using implicit representations. We also confirmed that proposed methods of deformation and visualization can be executed at sufficient quality and speed using commodity graphics hardware on a standard PC.

Implicit surfaces in 3D geometric modeling are limited to two manifolds because the corresponding implicit fields are usually defined by real-valued functions which bisect space into interior and exterior. We present a novel method of modeling non-manifold surfaces by implicit representation. Our method allows discontinuity of the field function and assesses the special meaning of the locus where the function is not differentiable. The enhancement can yield a non-manifold surface with such features as holes and boundaries. The discontinuous field function also enables multiple classification of the field, which makes it possible to represent branches and intersections of the implicit surfaces. The implicit field is polygonized by the algorithm based on the marching cubes algorithm, which is extended to treat discontinuous fields correctly. We also describe an efficient implementation of converting a surface model into a set of discrete samples of field function, and finally present the result of the non-manifold surfaces reproduced by our method.

We present an interactive method of visualizing both manifold and non-manifold implicit surfaces. The implicit surfaces are directly visualized at interactive frame rates independent of surface complexity by the hardware-accelerated volume rendering method. Although conventional implicit surfaces can represent only two-manifold surfaces, we have developed a technique of representing non-manifold surfaces as implicit surfaces by applying segmented distance field. Implicit surfaces represented by this definition can be rendered by pre-integrated volume rendering using vertex generation diagrams as pre-integration table. We also developed a system for visualizing the implicit surfaces and have confirmed that it can render surfaces at sufficient quality and speed.

A laser diode (LD) frequency separation locking method (called the reference pulse method) is proposed. This method has advantageous features for frequency division multiplexing (FDM) networks from the viewpoint of frequency separation stability with a strict frequency separation standard, modulation format independence, controllability over a large number of LDs, and frequency synchronization capability. Frequency locking experiments, using four and ten controlled LDs, confirmed that the control system using the method can stabilize frequency spacing for more than 100 LDs. The frequency fluctuation is suppressed to less than 10 MHz. Frequency synchronization, utilizing the reference pulse method, is proposed and demonstrated experimentally for two controlled LD groups, each consisting of three LDs. Frequency discrepancy between two LD groups was only 2.7% of the frequency separation. Required frequency-swept light power and controlled LD power at the detector input for frequency synchronization indicate that more than 50000 LD groups within a 10 km area, each having 100 LDs, can be synchronized simultaneously.>