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Dyslexia cause neurological limitations upon its patients such that they have poor phonological awareness and orthographical skills. This in turn limit the patients’ abilities to derive meaning from words which are keys to effective reading. To aid dyslexics in their comprehensions, a top-down approach to reading is proposed. In the meanwhile, a graphical model is also proposed as a tool to help researchers pinpoint neurological processes. It cleanly shows that the top-down approach could bypass dyslexic patients’ neurological limitations. It is also hypothesized that by aiding their understanding of articles and words, it is also possible for patients to improve their phonological awareness and orthographical skills. Our implementation to the research goals is VR reading, which uses multimedia feedback to give cues to dyslexic students on the meaning of words and articles. VR reading consists of aiding images, voice-overs, videos and a background theme dome that gives encapsulated cues on the meanings of the article and its words that are detached from the article itself. This is an important design decision as we want dyslexic students to rely more on multimedia feedback in deriving the meaning. We also show a preliminary evaluation which is a step towards testifying the aforementioned hypotheses with VR reading. It involves primary school children to read a Chinese article and be evaluated afterwards. The result seems to indicate that VR reading is useful in aiding students in their reading comprehension and additionally, has potential to improve their phonological awareness and orthographical skills.

Observing that a motion signal is decomposable into multiple levels, a video generation model which realizes this hypothesis is proposed. The model decomposes motion into a two-level signal involving a global path and local pattern. They are modeled via a latent path in the form of a composite Bezier spline along with a latent sine function respectively. In the application context, the model fills the research gap in its ability to connect an arbitrary number of input key frames smoothly. Experimental results indicate that the model improves in terms of the smoothness of the generated video. In addition, the ability of the model in separating global and local signal has been validated.

One crucial problem in VR is to establish a good correspondence between the virtual and physical scenes, while respecting the key structure and layout of the two spaces. A VR scene may well allow a user to move towards a certain direction, but in reality, a wall could block his/her path. The reason is that the virtual scene is often designed by designers for a large user population, being unable to consider individual physical constraints. Recent works involve redirected walking or additional VR hardware. We propose an alternative solution by adapting the virtual scene to the physical scene. The goal is to preserve the layout of the original design while allowing the virtual scene to be fully walkable. To move towards that goal, this paper proposes an object layout transfer mechanism to transfer an object layout from a virtual room to a physical room. A VR application can automatically transfer a designer’s virtual scene to fit any household room. Our solution involves key object layout features extraction and a multi-stage algorithm to shuffle the objects in the physical space. A user study is conducted to demonstrate that the proposed model is able to synthesize transferred layouts that appear to be created by a human designer.