Beyond K-12 education, there is a need to better address the learning methodologies of students to enable them to become independent self-directed problem solvers upon their graduation from tertiary studies. In this work, the preliminary studies and results for using a self-directed learning (SDL) approach for project-based learning (PBL) in the area of Information Technology is presented. Coupled with the adoption of interrelated dimensions of competency, the proposed work captures the learning journey including (1) the transition from pure software implementation of enacted scenarios to hands-on problem solving on the hardware equipment, and (2) the challenges and benefits of adapting this framework to expand the disposition components to achieve SDL. With the changes, students can reap the benefits of being more independent in solving realistic and situational problem practically, which will be advantageous for them upon joining the workforce. Early results from the implementation show positive responses from students in finding the SDL approach to be useful and suggest possible extension of its usage to other related areas of study.

In this paper, an image format named Virtual Character Animation Image (VCAI) is presented for providing an efficient form of representation for humanoid motion data. By mapping the VCA motion information as 2-D images, characteristics of joint's correlation for the skeletal avatar and temporal coherence within the motion data are jointly reflected as spatial correlation of an image to aid compression. Since the VCA is now encoded as an image, the use of image processing tools and image delivery techniques are now possible. Lastly, a modified motion filter (MMF) is proposed to minimize the visual discontinuity in VCA's motion due to the quantization and transmission noise at high compression rate. The MMF helps to remove high frequency noise components and smoothen the motion signal providing perceptually improved VCA with reduction in distortion. Simulation results demonstrate the effectiveness of the proposed scheme ensuring the minor degradation of VCA quality measured by objective error metric and perceptual loss to the VCA for highly compressed motion stream.

The use of realistic humanoid animations generated through motion capture (MoCap) technology is widespread across various 3-D applications and industries. However, the existing compression techniques for such representation often do not consider the implicit coherence within the anatomical structure of a human skeletal model and lacks portability for transmission consideration. In this paper, a novel concept virtual character animation image (VCAI) is proposed. Built upon a fuzzy clustering algorithm, the data similarity within the anatomy structure of a virtual character (VC) model is jointly considered with the temporal coherence within the motion data to achieve efficient data compression. Since the VCA is mapped as an image, the use of image processing tool is possible for efficient compression and delivery of such content across dynamic network. A modified motion filter (MMF) is proposed to minimize the visual discontinuity in VCA's motion due to the quantization and transmission error. The MMF helps to remove high frequency noise components and smoothen the motion signal providing perceptually improved VCA with lessened distortion. Simulation results show that the proposed algorithm is competitive in compression efficiency and decoded VCA quality against the state-of-the-art VCA compression methods, making it suitable for providing quality VCA animation to low-powered mobile devices.

In this paper, a technique for transmitting level of details motion sequences for virtual character animation is proposed. We have demonstrated that by using progressive level of details (LOD) scheme on the motion capture information, efficient LOD representation of the skeleton motion can be obtained. The proposed virtual character encoder is scalable in nature providing a form of flexibility for the bit-stream to be partially decodable at any bit rate within the bit rate range to address the dynamic bandwidth constraint of a heterogeneous wireless network. Based on the structural characteristic of the virtual character, the packet will be delivered across dynamic channel condition to provide the viewer with the best reconstructed virtual character's motion quality.

The transmission of 3D models in the form of Geometry Images (GI) is an emerging and appealing concept due to the reduction in complexity from R3 to image space and wide availability of mature image processing tools and standards. However, geometry images often suffer from the artifacts and error during compression and transmission. Thus, there is a need to address the artifact reduction, error resilience and protection of such data information during the transmission across an error prone network. In this paper, we introduce a new concept, called Spectral Geometry Images (SGI), which naturally combines the powerful spectral analysis with geometry images. We show that SGI is more effective than GI to generate visually pleasing shapes at high compression rates. Furthermore, by coupling SGI to the proposed error protection scheme, we are able to ensure the smooth delivery of 3D model across error networks for different packet loss rate simulated using the two-state Markov model.