The use of virtual reality (VR) has been exponentially increasing and due to that many researchers have started to work on developing new VR based social media. For this purpose it is important to have an avatar of the user which look like them to be easily generated by the devices which are accessible, such as mobile phones. In this paper, we propose a novel method of recreating a 3D human face model captured with a phone camera image or video data. The method focuses more on model shape than texture in order to make the face recognizable. We detect 68 facial feature points and use them to separate a face into four regions. For each area the best fitting models are found and are further morphed combined to find the best fitting models for each area. These are then combined and further morphed in order to restore the original facial proportions. We also present a method of texturing the resulting model, where the aforementioned feature points are used to generate a texture for the resulting model.
A modified emulsion polymerisation synthesis route for preparing highly dispersed cationic polystyrene (PS) nanoparticles is reported. The combined use of 2,2′-azobis[2-(2-imidazolin- 2-yl)propane] di-hydrochloride (VA-044) as the initiator and acetone/water as the solvent medium afforded successful synthesis of cationic PS particles as small as 31 nm in diameter. A formation mechanism for the preparation of PS nanoparticles was proposed, whereby the occurrence of rapid acetone diffusion caused spontaneous rupture of emulsion droplets into smaller droplets. Additionally, acetone helped to reduce the surface tension and increase the solubility of styrene, thus inhibiting aggregation and coagulation among the particles. In contrast, VA-044 initiator could effectively regulate the stability of the PS nanoparticles including both the surface charge and size. Other reaction parameters i.e. VA-044 concentration and reaction time were examined to establish the optimum polymerisation conditions.