Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: ,  develop an interactive Non-negative Matrix Factorization method for representative action video discovery. The original video is first evenly segmented into some short clips and the bag-of-words model is used to describe each clip. Then a temporal consistent Non-negative Matrix Factorization model is used for clustering and action segmentation. Since the clustering and segmentation results may not satisfy the user's intention, two extra human operations: MERGE and ADD are developed to permit user to improve the results. The newly developed interactive Non-negative Matrix Factorization method can therefore generate personalized results. Experimental results on the public izman dataset demonstrate that our approach is able to improve the action discovery and segmentation results.
['Hui Teng', 'Huaping Liu', 'Lianzhi Yu', 'Fuchun Sun']
I am writing a research paper on a idea Representative Video Action Discovery Using Interactive Non-negative Matrix Factorization
[{"from": "human", "value": "I am writing a research paper on a idea Representative Video Action Discovery Using Interactive Non-negative Matrix Factorization"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: ,  develop an interactive Non-negative Matrix Factorization method for representative action video discovery. The original video is first evenly segmented into some short clips and the bag-of-words model is used to describe each clip. Then a temporal consistent Non-negative Matrix Factorization model is used for clustering and action segmentation. Since the clustering and segmentation results may not satisfy the user's intention, two extra human operations: MERGE and ADD are developed to permit user to improve the results. The newly developed interactive Non-negative Matrix Factorization method can therefore generate personalized results. Experimental results on the public izman dataset demonstrate that our approach is able to improve the action discovery and segmentation results."}]