Stereo images have been captured primarily for 3D reconstruction in the past. However, the depth information acquired from stereo can also be used along with saliency to highlight certain objects in a scene.
In this project we derive a computational strategy to enhance the performance of Image Quality Metrics (IQM) by using content specific features of an image. We do this by creating Visual Error Importance (VEI) map that is applied to the error maps computed by the IQM. A global optimization can be used to compute the VEI map that is optimal for any given IQM from a set of simple image features..
In this study, we use data captured by smart sensors to deploy a Cloud Computing Interface in the Cloud infrastructure (CCI). To achieve the benefit from processing, analyzing, evaluating and storing fine motion data.
The research goal is to develop treatments that can slow or halt the progression of the disease before it significantly affects quality of life. As a computing science research, my plan is to facilitate early diagnosis.
