Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Hair is an important aspect of human appearance. Hair color has been employed to facilitate face retrieval in literature, but hair style is still dismissed because of the challenges of its segmentation. ,  propose a novel hair style retrieval algorithm in unconstrained environments. In contrary to defining similarity based on features,  base our measurement directly on hair shapes. To bridge the “semantic gap” beten low-level features and high-level hairstyle,  incorporate mapping function which integrates local and pairwise evidences in MRF framework. Additionally,  propose a RankBoost learning algorithm to select the most informative patches integrating the heuristic information of mapping function accuracy. Our method is applied to the “Labeled Faces in the Wild” dataset and yields promising results.
['Nan Wang', 'Haizhou Ai']
I am writing a research paper on a idea Hair style retrieval by semantic mapping on informative patches
[{"from": "human", "value": "I am writing a research paper on a idea Hair style retrieval by semantic mapping on informative patches"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Hair is an important aspect of human appearance. Hair color has been employed to facilitate face retrieval in literature, but hair style is still dismissed because of the challenges of its segmentation. ,  propose a novel hair style retrieval algorithm in unconstrained environments. In contrary to defining similarity based on features,  base our measurement directly on hair shapes. To bridge the \u201csemantic gap\u201d beten low-level features and high-level hairstyle,  incorporate mapping function which integrates local and pairwise evidences in MRF framework. Additionally,  propose a RankBoost learning algorithm to select the most informative patches integrating the heuristic information of mapping function accuracy. Our method is applied to the \u201cLabeled Faces in the Wild\u201d dataset and yields promising results."}]