Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: dding is one of the most important ceremonies in our lives. It symbolizes the birth and creation of a new family. ,  present a system for automatically segmenting a dding ceremony video into a sequence of recognizable dding events, e.g., the couple's dding kiss. Our goal is to develop an automatic tool that helps users to efficiently organize, search, and retrieve his/her treasured dding memories. Furthermore, the obtained event descriptions could benefit and complement the current research in semantic video understanding. Based on the knowledge of dding customs, a set of audiovisual features, relating to the dding contexts of speech/music types, applause activities, picture-taking activities, and leading roles, are exploited to build statistical models for each dding event. Thirteen dding events are then recognized by a hidden Markov model, which takes into account both the fitness of observed features and the temporal rationality of event ordering to improve the segmentation accuracy.  conducted experiments on a collection of dding videos and the promising results demonstrate the effectiveness of our approach. Comparisons with conditional random fields show that the proposed approach is more effective in this application domain.
['Wen-Huang Cheng', 'Yung-Yu Chuang', 'Yin-Tzu Lin', 'Chi-Chang Hsieh', 'Shao-Yen Fang', 'Bing-Yu Chen', 'Ja-Ling Wu']
I am writing a research paper on a idea Semantic Analysis for Automatic Event Recognition and Segmentation of Wedding Ceremony Videos
[{"from": "human", "value": "I am writing a research paper on a idea Semantic Analysis for Automatic Event Recognition and Segmentation of Wedding Ceremony Videos"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: dding is one of the most important ceremonies in our lives. It symbolizes the birth and creation of a new family. ,  present a system for automatically segmenting a dding ceremony video into a sequence of recognizable dding events, e.g., the couple's dding kiss. Our goal is to develop an automatic tool that helps users to efficiently organize, search, and retrieve his/her treasured dding memories. Furthermore, the obtained event descriptions could benefit and complement the current research in semantic video understanding. Based on the knowledge of dding customs, a set of audiovisual features, relating to the dding contexts of speech/music types, applause activities, picture-taking activities, and leading roles, are exploited to build statistical models for each dding event. Thirteen dding events are then recognized by a hidden Markov model, which takes into account both the fitness of observed features and the temporal rationality of event ordering to improve the segmentation accuracy.  conducted experiments on a collection of dding videos and the promising results demonstrate the effectiveness of our approach. Comparisons with conditional random fields show that the proposed approach is more effective in this application domain."}]