Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Driven by recent advances in human-centered computing, Facial Expression Recognition (FER) has attracted significant attention in many applications. ,  propose a novel graphical model, multi-level Transformed Dirichlet Process (ml-TDP), for multi-pose FER. In our approach, pose is explicitly introduced into ml-TDP so that separate training and parameter tuning for each pose is not required. In addition, ml-TDP can learn an intermediate facial expression representation subject to geometric constraints. By sharing the pool of spatially-coherent features over expressions and poses,  provide a scalable solution for multi-pose FER. Extensive experimental result on benchmark facial expression databases shows the superior performance of ml-TDP.
['Feifei Zhang', 'Qirong Mao', 'Ming Dong', 'Yongzhao Zhan']
I am writing a research paper on a idea Multi-pose Facial Expression Recognition Using Transformed Dirichlet Process
[{"from": "human", "value": "I am writing a research paper on a idea Multi-pose Facial Expression Recognition Using Transformed Dirichlet Process"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Driven by recent advances in human-centered computing, Facial Expression Recognition (FER) has attracted significant attention in many applications. ,  propose a novel graphical model, multi-level Transformed Dirichlet Process (ml-TDP), for multi-pose FER. In our approach, pose is explicitly introduced into ml-TDP so that separate training and parameter tuning for each pose is not required. In addition, ml-TDP can learn an intermediate facial expression representation subject to geometric constraints. By sharing the pool of spatially-coherent features over expressions and poses,  provide a scalable solution for multi-pose FER. Extensive experimental result on benchmark facial expression databases shows the superior performance of ml-TDP."}]