Pemodelan 3D Senjata Tradisional Untuk GAMERPG Pengenalan Budaya Indonesia "SI BOLANG" dengan Metode Blueprint dan Seamless Unwrapping Material

Game "si Bolang" merupakan game edukasi yang dirancang untuk pengenalan Budaya Indonesia. Senjata tradisional merupakan senjata yang dibangun dengan bentuk yang sama dari generasi ke generasi yang menjadi ciri khas setiap suku daerah. Permasalahan yang diselesaikan dalam penelitian ini adalah belum adanya aset 3D senjata tradisional Indonesia untuk pengembangan game "si Bolang" sehingga dibangun pemodelan 3D yang mendekati bentuk aslinya. Tujuan penelitian ini adalah menghasilkan objek 3D senjata tradisional Indonesia yang dapat digunakan untuk pengembangan game "si Bolang" dan menghasilkan model 3D yang menyerupai bentuk objek aslinya. Pemodelan 3D senjata tradisional dibuat menggunakan metode Blueprint dan seaemless unwrappingmaterial. Kedua metode ini menggunakan agar mempermudah dalam proses pembuatan model senjata tradisional. Texturing menggunakan metode seamless unwrapping material adalah dengan membuka face model 3D lalu dilanjutkan dengan menerapkan foto asli atau foto referensi sebagai texture. Penelitian ini menghasilkan model 3D senjata tradisional yang diterima oleh tim pengembang game "si Bolang" dan dikatakan mirip oleh ahli multimedia. Pengujian alphamenghasilkan 76% sangat setuju, 24% setuju, 0% kurang setuju, dan 0% tidak setuju. Pengujian ahli multimedia mendapatkan skor 66% sangat mirip, 33% mirip, 0% tidak mirip, dan 0% sangat tidak miri

Interactive removal and ground truth for difficult shadow scenes

A user-centric method for fast, interactive, robust, and high-quality shadow removal is presented. Our algorithm can perform detection and removal in a range of difficult cases, such as highly textured and colored shadows. To perform detection, an on-the-fly learning approach is adopted guided by two rough user inputs for the pixels of the shadow and the lit area. After detection, shadow removal is performed by registering the penumbra to a normalized frame, which allows us efficient estimation of nonuniform shadow illumination changes, resulting in accurate and robust removal. Another major contribution of this work is the first validated and multiscene category ground truth for shadow removal algorithms. This data set containing 186 images eliminates inconsistencies between shadow and shadow-free images and provides a range of different shadow types such as soft, textured, colored, and broken shadow. Using this data, the most thorough comparison of state-of-the-art shadow removal methods to date is performed, showing our proposed algorithm to outperform the state of the art across several measures and shadow categories. To complement our data set, an online shadow removal benchmark website is also presented to encourage future open comparisons in this challenging field of research

Numerical and Geometric Optimizations for Surface and Tolerance Modeling

Optimization techniques are widely used in many research and engineering areas. This dissertation presents numerical and geometric optimization methods for solving geometric and solid modeling problems. Geometric optimization methods are designed for manufacturing process planning, which optimizes the process by changing dependency relationships among geometric primitives from the original design diagram. Geometric primitives are used to represent part features, and dependencies in the dimensions between parts are represented by a topological graph. The ordering of these dependencies can have a significant effect on the tolerance zones in the part. To obtain tolerance zones from the dependencies, the conventional parametric method of tolerance analysis is de-composed into a set of geometric computations, which are combined and cascaded to obtain the tolerance zones in the geometric representations. Geometric optimization is applied to the topological graph in order to find a solution that provides not only an optimal dimensioning scheme but also an optimal plan for manufacturing the physical part. The applications of our method include tolerance analysis, dimension scheme optimization, and process planning. Two numerical optimization methods are proposed for local and global surface parameterizations. One is the nonlinear optimization, which is used for building the local field-aware parameterization. Given a local chart of the surface, a two-phase method is proposed, which generates a folding-free parameterization while still being aware of the geodesic metric. The parameterization method is applied in a view-dependent 3D painting system, which constitutes a local, adaptive and interactive painting environment. The other is the mixed-integer quadratic optimization, which is used for generating a quad mesh from a given triangular mesh. With a given cross field, the computation of parametric coordinates is formulated to be a mixed-integer optimization problem, which parameterizes the surface with good quality by adding redundant integer variables. The mixed integer system is solved more efficiently by an improved adaptive rounding solver. To obtain the final quadrangular mesh, an isoline tracing method and a breadth-first traversal mesh generation method are proposed so that the final mesh result has face information, which is useful for further model processing

Development of 3D models, animations, storyline and dialogue system for interactive English learning mobile game for Russian speaking users

https://www.ester.ee/record=b5148750*es

Pemodelan 3D Senjata Tradisional Untuk GAMERPG Pengenalan Budaya Indonesia "SI BOLANG" dengan Metode Blueprint dan Seamless Unwrapping Material

Game "si Bolang" merupakan game edukasi yang dirancang untuk pengenalan Budaya Indonesia. Senjata tradisional merupakan senjata yang dibangun dengan bentuk yang sama dari generasi ke generasi yang menjadi ciri khas setiap suku daerah. Permasalahan yang diselesaikan dalam penelitian ini adalah belum adanya aset 3D senjata tradisional Indonesia untuk pengembangan game "si Bolang" sehingga dibangun pemodelan 3D yang mendekati bentuk aslinya. Tujuan penelitian ini adalah menghasilkan objek 3D senjata tradisional Indonesia yang dapat digunakan untuk pengembangan game "si Bolang" dan menghasilkan model 3D yang menyerupai bentuk objek aslinya. Pemodelan 3D senjata tradisional dibuat menggunakan metode Blueprint dan seaemless unwrappingmaterial. Kedua metode ini menggunakan agar mempermudah dalam proses pembuatan model senjata tradisional. Texturing menggunakan metode seamless unwrapping material adalah dengan membuka face model 3D lalu dilanjutkan dengan menerapkan foto asli atau foto referensi sebagai texture. Penelitian ini menghasilkan model 3D senjata tradisional yang diterima oleh tim pengembang game "si Bolang" dan dikatakan mirip oleh ahli multimedia. Pengujian alphamenghasilkan 76% sangat setuju, 24% setuju, 0% kurang setuju, dan 0% tidak setuju. Pengujian ahli multimedia mendapatkan skor 66% sangat mirip, 33% mirip, 0% tidak mirip, dan 0% sangat tidak mirip</span

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

Interactive Shadow Removal and Ground Truth for Variable Scene Categories

We present an interactive, robust and high quality method for fast shadow removal. To perform detection we use an on-the-fly learning approach guided by two rough user inputs for the pixels of the shadow and the lit area. From this we derive a fusion image that magnifies shadow boundary intensity change due to illumination variation. After detection, we perform shadow removal by registering the penumbra to a normalised frame which allows us to efficiently estimate non-uniform shadow illumination changes, resulting in accurate and robust removal. We also present the first reliable, validated and multi-scene category ground truth for shadow removal algorithms which overcomes limitations in existing data sets -- such as inconsistencies between shadow and shadow-free images and limited variations of shadows. Using our data, we perform the most thorough comparison of state of the art shadow removal methods to date. Our algorithm outperforms the state of the art, and we supply our P-code and evaluation data and scripts to encourage future open comparisons

Signal-Specialized Parameterization

To reduce memory requirements for texture mapping a model, we build a surface parametrization specialized to its signal (such as color or normal). Intuitively, we want to allocate more texture samples in regions with greater signal detail. Our approach is to minimize signal approximation error --- the difference between the original surface signal and its reconstruction from the sampled texture. Specifically, our signal-stretch parametrization metric is derived from a Taylor expansion of signal error. For fast evaluation, this metric is pre-integrated over the surface as a metric tensor. We minimize this nonlinear metric using a novel coarse-to-fine hierarchical solver, further accelerated with a fine-to-coarse propagation of the integrated metric tensor. Use of metric tensors permits anisotropic squashing of the parametrization along directions of low signal gradient. Texture area can often be reduced by a factor of 4 for a desired signal accuracy compared to non-specialized parametrizations.Engineering and Applied Science

Capturing and Reconstructing the Appearance of Complex {3D} Scenes

In this thesis, we present our research on new acquisition methods for reflectance properties of real-world objects. Specifically, we first show a method for acquiring spatially varying densities in volumes of translucent, gaseous material with just a single image. This makes the method applicable to constantly changing phenomena like smoke without the use of high-speed camera equipment. Furthermore, we investigated how two well known techniques -- synthetic aperture confocal imaging and algorithmic descattering -- can be combined to help looking through a translucent medium like fog or murky water. We show that the depth at which we can still see an object embedded in the scattering medium is increased. In a related publication, we show how polarization and descattering based on phase-shifting can be combined for efficient 3D~scanning of translucent objects. Normally, subsurface scattering hinders the range estimation by offsetting the peak intensity beneath the surface away from the point of incidence. With our method, the subsurface scattering is reduced to a minimum and therefore reliable 3D~scanning is made possible. Finally, we present a system which recovers surface geometry, reflectance properties of opaque objects, and prevailing lighting conditions at the time of image capture from just a small number of input photographs. While there exist previous approaches to recover reflectance properties, our system is the first to work on images taken under almost arbitrary, changing lighting conditions. This enables us to use images we took from a community photo collection website