Abdullah Zawawi’s research while affiliated with University of Science Malaysia and other places

Whether we like it or not, digital gaming and social networking are already wide-spread activities in our culture. More and more homes are now equipped with video-game consoles, computers, tablets or smart phones. The main purpose of this paper is to present an outcome of a preliminary studies done in exploring the current use of digital games in teaching and learning. This article will discuss how digital games can be used in our education systems and the main benefits of venturing into this research area. Initial investigation suggests that this proposed research will be able to answer those questions about learning games and may help plot an educational design model or guidelines for people and organizations who are interested in developing or fos-tering the development of digital games for learning.

A point data set is a set of independent point samples that are typically acquired from a D scanning process. We are interested in detecting and rendering silhouettes in such data set, for the purpose of Non-Photorealistic Rendering (NPR). Traditionally, work on silhouette extraction and rendering tends to assume a polygonal mesh input, where connectivity information is available and the formation of silhouettes involves tracking of edges. A point data set, however, does not contain connectivity information. In a previous paper (38), we presented the first hybrid image/object-space method to directly detect and render silhouettes for point data set. In this paper, we describe the essence of the method in more detail, emphasizing on the mathematics applied. We describe as well a simple variant of the method to detect silhouette points using ray casting instead of point splatting. This variant is useful in the absence of dedicated graphics hardware.

We present in this paper a framework for free-form deformation of point-based geometry. To perform the deformation, we propose a sketch-based user interface similar to that described in Teddy [8]. To prevent tearing up of under-sampled surface regions due to large-scale free-form deformation of the geometry, we describe a simple and effective procedure to insert new sample points into the affected region. This is, in fact, the core of our framework. Prior to the deformation, for each point that is involved in the deformation, we store its set of neighboring points. After the deformation, we retrieve the cached neighboring points and process it to form a triangle fan that approximates the local deformed surface. New point samples are then sampled within the triangles. Finally to prevent self-intersection after the deformation process, we propose a simple approach based on a binary volume data structure.