Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The clustering-based approach for detecting abnormalities in surveillance video requires the appropriate definition of similarity beten events. The HMM-based similarity defined previously falls short in handling the overfitting problem.  propose in this paper a multi-sample-based similarity measure, where HMM training and distance measuring are based on multiple samples. These multiple training data are acquired by a novel dynamic hierarchical clustering (DHC) method. By iteratively reclassifying and retraining the data groups at different clustering levels, the initial training and clustering errors due to overfitting will be sequentially corrected in later steps. Experimental results on real surveillance video show an improvement of the proposed method over a baseline method that uses single-sample-based similarity measure and spectral clustering.
['Fan Jiang', 'Ying Wu', 'Aggelos K. Katsaggelos']
I am writing a research paper on a idea Abnormal Event Detection from Surveillance Video by Dynamic Hierarchical Clustering
[{"from": "human", "value": "I am writing a research paper on a idea Abnormal Event Detection from Surveillance Video by Dynamic Hierarchical Clustering"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The clustering-based approach for detecting abnormalities in surveillance video requires the appropriate definition of similarity beten events. The HMM-based similarity defined previously falls short in handling the overfitting problem.  propose in this paper a multi-sample-based similarity measure, where HMM training and distance measuring are based on multiple samples. These multiple training data are acquired by a novel dynamic hierarchical clustering (DHC) method. By iteratively reclassifying and retraining the data groups at different clustering levels, the initial training and clustering errors due to overfitting will be sequentially corrected in later steps. Experimental results on real surveillance video show an improvement of the proposed method over a baseline method that uses single-sample-based similarity measure and spectral clustering."}]