Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: It is challenging to track multiple facial features simultaneously when rich expressions are presented on a face.  propose a two-step solution. In the first step, several independent condensation-style particle filters are utilized to track each facial feature in the temporal domain. Particle filters are very effective for visual tracking problems; hover multiple independent trackers ignore the spatial constraints and the natural relationships among facial features. In the second step,  use Bayesian inference--belief propagation--to infer each facial feature's contour in the spatial domain, in which  learn the relationships among contours of facial features beforehand with the help of a large facial expression database. The experimental results show that our algorithm can robustly track multiple facial features simultaneously, while there are large interframe motions with expression changes.
['Congyong Su', 'Li Huang']
I am writing a research paper on a idea Spatio-temporal graphical-model-based multiple facial feature tracking
[{"from": "human", "value": "I am writing a research paper on a idea Spatio-temporal graphical-model-based multiple facial feature tracking"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: It is challenging to track multiple facial features simultaneously when rich expressions are presented on a face.  propose a two-step solution. In the first step, several independent condensation-style particle filters are utilized to track each facial feature in the temporal domain. Particle filters are very effective for visual tracking problems; hover multiple independent trackers ignore the spatial constraints and the natural relationships among facial features. In the second step,  use Bayesian inference--belief propagation--to infer each facial feature's contour in the spatial domain, in which  learn the relationships among contours of facial features beforehand with the help of a large facial expression database. The experimental results show that our algorithm can robustly track multiple facial features simultaneously, while there are large interframe motions with expression changes."}]