A Flexible Goal Of Understanding Of The Human Face And Motion Analysis Technology-oriented Research

Image interpretation, video motion estimation and analysis is the key problems of computer vision and have attracted intense interest of many researchers. Till now a great deal of algorithms have been proposed and show potential good result in many applications throughout the people's woking and living.This thesis is focus on image interpretation and motion analysis. A system of full automatic face interpretation and motion analysis is set up, which can be devided into three sub fields: face interpretation, face region motion estimation and face feature points tracking.In face image interpretation we select ASM/AAM as the basis, make many good generalization and successfully apply it to the face image, which the result shows the efficiency and robustness of the algorithm. In motion estimation and analysis we make a full analysis of L-K algorithm and generilize it to the inverse compositional algorithm, which can track the moving object real time and support any image worping. For face feature points tracking we introduce the uncertainty factorization, subspace optical flow estimation and fuse the idea of the inverse compositional algorithm. As a result an efficient and robust algorithm is presented in the thesis. The proposed algorithm has been proven by experiments that it can properly track points with the degeneration textures, which have only ID or even little texture. Thus it provides a unified approach for tracking corner-like points together with points along linear structures in the image. It also provides semi-dense correspondence, which is one of the key problems of SFM. The image interpretation and motion estimation result can be also potentially used in object-based video coding.In the thesis we have an insight view of statistical models, covariance weighted and subspace constraint optical flow and successfully apply these technologies in the system of automatic face interpretation and motion analysis. It is also worth noting that this technology not only can be used for face but also for a class of rigid/nomigid objects, such as hand, car and so on.