Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Advances in computing, networking, and multimedia technologies have led to a tremendous growth of sports video content and accelerated the need of analysis and understanding of sports video content. Sports video analysis has been a hot research area and a number of potential applications have been identified. ,  summarize our research achievement on semantics extraction and automatic editorial content creation and adaptation in sports video analysis.  first propose a generic multi-layer and multi-modal framework for sports video analysis. Then  introduce several mid-level audio/visual features which are able to bridge the semantic gap beten low-level features and high-level understanding.  also discuss emerging applications on editorial content creation and content enhancement/adaptation in sports video analysis, including event detection, sports MTV generation, automatic broadcast video generation, tactic analysis, player action recognition, virtual content insertion, and mobile sports video adaptation. Finally,  identify future directions in terms of research challenges remained and real applications expected.
['Changsheng Xu', 'Jian Cheng', 'Yi Zhang', 'Yifan Zhang', 'Hanqing Lu']
I am writing a research paper on a idea Sports Video Analysis: Semantics Extraction, Editorial Content Creation and Adaptation
[{"from": "human", "value": "I am writing a research paper on a idea Sports Video Analysis: Semantics Extraction, Editorial Content Creation and Adaptation"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Advances in computing, networking, and multimedia technologies have led to a tremendous growth of sports video content and accelerated the need of analysis and understanding of sports video content. Sports video analysis has been a hot research area and a number of potential applications have been identified. ,  summarize our research achievement on semantics extraction and automatic editorial content creation and adaptation in sports video analysis.  first propose a generic multi-layer and multi-modal framework for sports video analysis. Then  introduce several mid-level audio/visual features which are able to bridge the semantic gap beten low-level features and high-level understanding.  also discuss emerging applications on editorial content creation and content enhancement/adaptation in sports video analysis, including event detection, sports MTV generation, automatic broadcast video generation, tactic analysis, player action recognition, virtual content insertion, and mobile sports video adaptation. Finally,  identify future directions in terms of research challenges remained and real applications expected."}]