Kok-Why Ng

A practical implementation of a 3D game engine

Creating a 3D game engine is not a trivial task as gamers often demand for high quality output with top notch performance in games. In this paper, we show how various real-time rendering algorithms can be applied to implement a practical 3D game engine. We explore the general architecture of a 3D engine and discuss the role of a scene graph in a 3D engine. We look at scene graph from the software engineering perspective. In particular, we show the way to design a scene graph that is object-oriented and portable across different rendering engine. Then, we explain the algorithms that we apply to speed up the performance of our 3D engine. We optimize the 3D engine on the scene graph and object geometry levels. The algorithms that we propose are expected to perform reasonably well for both static and dynamic scenes. Finally, we give a brief preview on the possibility of parallel processing in scene graph to create a 3D engine with multiprocessing capability.

An unobtrusive Android person verification using accelerometer based gait

Mobile devices are ubiquitous enough to be considered as a valid token for proof of claim to identity. Unfortunately, the small size of mobile devices also means that it is prone to being misplaced and stolen. Gait biometric on accelerometer equipped mobile devices can add another layer of security in the event of theft, as it would refute a fraudulent claim to identity. As an extra bonus, gait data can be collected without the knowledge of the person handling the mobile device. In this paper, we describe how mobile devices can be used unobtrusively for the purpose of person verification. Person verification is achieved by classification of accelerometer based gait data recorded by said mobile device. Use cases for this approach is presented in a framework; supported by proof of concept experimental results.

MMU GASPFA: A COTS multimodal biometric database

This paper describes the baseline corpus of a new multimodal biometric database, the MMU GASPFA (Gait-Speech-Face) database. The corpus in GASPFA is acquired using commercial off the shelf (COTS) equipment including digital video cameras, digital voice recorder, digital camera, Kinect camera and accelerometer equipped smart phones. The corpus consists of frontal face images from the digital camera, speech utterances recorded using the digital voice recorder, gait videos with their associated data recorded using both the digital video cameras and Kinect camera simultaneously as well as accelerometer readings from the smart phones. A total of 82 participants had their biometric data recorded. MMU GASPFA is able to support both multimodal biometric authentication as well as gait action recognition. This paper describes the acquisition setup and protocols used in MMU GASPFA, as well as the content of the corpus. Baseline results from a subset of the participants are presented for validation purposes.

Adaptive Model Simplification in Real-Time Rendering for Visualization

In this paper, we propose four different geometric measures to identify appropriate triangles to be simplified in 3D complex model. Each measure yields different weight on the same surface and produces a unique simplified model that worth to be analyzed. The proposed measures involve consideration on the resulting of the surfaces collapse, the high peak and low peak of the triangles mesh, the irregular triangle shape, the capacity and boundary view on the triangles mesh. The chosen triangle is to be collapsed based criterion on Half-edge Collapse Transformation method. From the empirical results, one of the proposed measures presents almost excellence in all the criteria mentioned above. The empirical results include the quality of the surface models (visualization purpose), the efficiency of the measures and the overall appearance preservation of the simplified models. The proposed measures are then to be compared to three existing measures. From the analyzed results, we combine the measures to adapt to the user’s response for generating the user-desired simplified models.

Improvement in decimation of triangle meshes for level of detail

Simplifying polygonal models to achieve a constant frame rate or to generate an ideal size of an object proportional to its viewing distance is one of the many techniques used in 3D visualizations these days. In this paper, we have selected a decimation algorithm to be further enhanced by introducing other techniques to obtain a better output. In our technique, parts of the characterization vertices are identified and further analyzed. In the boundary convex group, categorization is made whether the vertex is to be deleted or preserved. In the evaluation stage of the decimation algorithm, we use the singular value decomposition algorithm to compute the smallest eigenvector from a matrix formed from the surrounding neighboring vertices of the simple candidate vertices. Finally, in the triangulation stage, a careful and simple patching step is applied to the resulting holes so that the output would be balance in sizes. A balanced size refers to re-generating triangle-strips of similar size of the edges for a smoother model viewing.

Semi-automatic segmentation of 3d point clouds skeleton without explicit computation for critical points

Segmentation of 3D point clouds is vigorously discussed in recent years. Many existing techniques pre-process the data to identify critical points for meaningful features. Very often, the critical points are predicted at curvature objects and this does not always generate promising outcome. This paper proposes to segment the point clouds based on its skeleton as this robustly reflects the global shape of an object. The skeleton is constructed via Laplacian-based contraction method. Spherical approach is applied along the skeleton to segment the point clouds. The entire process is automatic. Only moderate user-input is applied to align the skeleton to the object. The output of the proposed method is to be compared with another popular segmentation method with critical points input. The result shows that the proposed method generates more accurate segmented features.

Surface reconstruction from the point cloud - A considerable framework

Three-dimensional (3D) surface reconstruction from the point cloud has been widely discussed since two decades ago. The existing methods are either incredibly complex in computation or the quality of the meshes is improved only after the surfaces are constructed. In this paper, we propose a considerable framework to trade off between quality and complexity for reconstructing the surfaces. We suggest revising the input point data before initiating the process of surface reconstruction for producing smooth surfaces. Our algorithm includes eliminating the alien points, which possibly produce crumple meshes. This piece of work is supported by several geometric measures which evidently tackle the objectives above. The prototype is hitherto under implementation phase. But we believe our proposed framework is worth a sharing among the researchers.