In this project, I use a reference image for calculating the ‘Image Transformation’ parameters (Centroids, Translation Vector, Covariance Matrices, Principal Axes and Rotation Angle) to transform the Image (02 in the picture). This is particularly useful in Medical Imaging domain to compare and align images with an atlas image for further examination (in this case, Brain Scans) .
I completed this project as a part of my ‘Medical Image Analysis’ coursework. I used ‘Active Contours’ image segmentation technique for segmenting the required part of the brain scan obtained using MRI.
The ‘Senescence’ framework is a character simulation plug-in for Maya that can be used for rigging and skinning muscle deformer based humanoid characters with support for aging. The framework was developed using Python, Maya Embedded Language and PyQt. The main targeted users for this framework are the Character Technical Directors, Technical Artists, Riggers and Animators from the production pipeline of Visual Effects Studios. The characters that were simulated using ‘Senescence’ were studied using a survey to understand how well the intended age was perceived by the audience. The results of the survey could not reject one of our null hypotheses which means that the difference in the simulated age groups of the character is not perceived well by the participants. But, there is a difference in the perception of simulated age in the character between an Animator and a Non-Animator. Therefore, the difference in the simulated character’s age was perceived by an untrained audience, but the audience was unable to relate it to a specific age group.