Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Captions in videos provide much useful semantic information for indexing and retrieving video contents. ,  present an effective approach to extracting captions from videos. Its novelty comes from exploiting the temporal information in both localization and segmentation of captions. Since some simple features such as edges, corners and color are utilized, our approach is efficient. It involves four steps. First,  exploit the distribution of corners to spatially detect and locate the caption in a frame. Then the temporal localization for different captions in a video is performed by identifying the change of stroke directions. After that,  segment the caption pixels in a clip with a same caption based on the consistency and dominant distribution of caption color. Finally, the segmentation results are further refined. The experimental results on two representative movies have preliminarily verified the validity of our approach.
['Xiaoqian Liu', 'Weiqiang Wang']
I am writing a research paper on a idea Extracting captions from videos using temporal feature
[{"from": "human", "value": "I am writing a research paper on a idea Extracting captions from videos using temporal feature"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Captions in videos provide much useful semantic information for indexing and retrieving video contents. ,  present an effective approach to extracting captions from videos. Its novelty comes from exploiting the temporal information in both localization and segmentation of captions. Since some simple features such as edges, corners and color are utilized, our approach is efficient. It involves four steps. First,  exploit the distribution of corners to spatially detect and locate the caption in a frame. Then the temporal localization for different captions in a video is performed by identifying the change of stroke directions. After that,  segment the caption pixels in a clip with a same caption based on the consistency and dominant distribution of caption color. Finally, the segmentation results are further refined. The experimental results on two representative movies have preliminarily verified the validity of our approach."}]