Abstract
The most important information in transforming a 2D image into a 3D image is the depth of each pixel in the image. However, a normal 2D image usually does not contain the depth information, which makes the transformation impossible. On the other hand, for some specific pictures, such as personal portraits, it is possible to infer crude depth information from their known contexts and properties. If we want to port this technology to embedded systems, we should further consider the performance and power consumption issues. This thesis presents a power-aware, 2D-to-3D image transformation tool for personal portraits on embedded systems, such as cell phones or personal information devices (PIDs). The tool first chooses a suitable depth-map generation algorithm based on the remaining power of the device. The depth map is then used to generate stereo binocular image pairs by the DIBR method. Finally, the two-eye views are merged to product a 3D image. Our experimental results show that the proposed method can produce a satisfactory stereoscopic effect.