Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In sparse representation based face recognition systems, the dictionary is assumed to be trained using ll-controlled face images. Many classic and contemporary face recognition algorithms work ll under the assumption, but degrade sharply when they are used in a real recognition system. This is mostly due to the fact that, in real-world scenarios, the training faces often appear to be loosely controlled, which are with different poses, occlusions and lighting conditions. ,  propose a method to simultaneously handle the difficulties mentioned above. Our method eliminates the pose ambiguity and the effect of occlusion and illumination by imposing spatial and temporal structure constraints, respectively. Experimental results on both synthetic and real data demonstrate the efficacy of our proposed method.
['Xiaojie Guo', 'Dongdai Lin']
I am writing a research paper on a idea Robust face image alignment using structural priors
[{"from": "human", "value": "I am writing a research paper on a idea Robust face image alignment using structural priors"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In sparse representation based face recognition systems, the dictionary is assumed to be trained using ll-controlled face images. Many classic and contemporary face recognition algorithms work ll under the assumption, but degrade sharply when they are used in a real recognition system. This is mostly due to the fact that, in real-world scenarios, the training faces often appear to be loosely controlled, which are with different poses, occlusions and lighting conditions. ,  propose a method to simultaneously handle the difficulties mentioned above. Our method eliminates the pose ambiguity and the effect of occlusion and illumination by imposing spatial and temporal structure constraints, respectively. Experimental results on both synthetic and real data demonstrate the efficacy of our proposed method."}]