Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: It is particularly important for surveillance systems to track the number of people in crowded scenes. ,  look into this problem of counting people in crowded scenes and propose a framework that fuses information coming from detection, tracking and region regres- sion together. For counting by regression,  propose to use region covari- ance features in the form of Sigma Sets in conjunction with interest point features. Experimental results on two benchmark datasets demonstrate that using region covariance features for the purpose of people counting yields effective results. Moreover, our results indicate that fusing detec- tion and regression is beneficial for more accurate people counting in crowded scenes.
['Cemil Zalluhoglu', 'Nazli Ikizler-Cinbis']
I am writing a research paper on a idea Counting People in Crowded Scenes via Detection and Regression Fusion
[{"from": "human", "value": "I am writing a research paper on a idea Counting People in Crowded Scenes via Detection and Regression Fusion"}, {"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 particularly important for surveillance systems to track the number of people in crowded scenes. ,  look into this problem of counting people in crowded scenes and propose a framework that fuses information coming from detection, tracking and region regres- sion together. For counting by regression,  propose to use region covari- ance features in the form of Sigma Sets in conjunction with interest point features. Experimental results on two benchmark datasets demonstrate that using region covariance features for the purpose of people counting yields effective results. Moreover, our results indicate that fusing detec- tion and regression is beneficial for more accurate people counting in crowded scenes."}]