Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: ,  deal with the problem of detecting the existence and the location of salient objects for thumbnail images on which most search engines usually perform visual analysis in order to handle b-scale images. Different from previous techniques, such as sliding window-based or segmentation-based schemes for detecting salient objects,  propose to use a learning approach, random forest in our solution. Our algorithm exploits global features from multiple saliency indicators to directly predict the existence and the position of the salient object. To validate our algorithm,  constructed a large image database collected from Bing image search, that contains hundreds of thousands of manually labeled b images. The experimental results using this new database and the resized MSRA database [16] demonstrate that our algorithm outperforms previous state-of-the-art methods.
['Peng Wang', 'Jingdong Wang', 'Gang Zeng', 'Jie Feng', 'Hongbin Zha', 'Shipeng Li']
I am writing a research paper on a idea Salient object detection for searched web images via global saliency
[{"from": "human", "value": "I am writing a research paper on a idea Salient object detection for searched web images via global saliency"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: ,  deal with the problem of detecting the existence and the location of salient objects for thumbnail images on which most search engines usually perform visual analysis in order to handle b-scale images. Different from previous techniques, such as sliding window-based or segmentation-based schemes for detecting salient objects,  propose to use a learning approach, random forest in our solution. Our algorithm exploits global features from multiple saliency indicators to directly predict the existence and the position of the salient object. To validate our algorithm,  constructed a large image database collected from Bing image search, that contains hundreds of thousands of manually labeled b images. The experimental results using this new database and the resized MSRA database [16] demonstrate that our algorithm outperforms previous state-of-the-art methods."}]