Hooligan detection: The effects of saliency and expert knowledge
Hooligan detection: The effects of saliency and expert knowledge
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流氓检测：显着性和专业知识的影响
DOI：
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发表时间：
2010
期刊：
影响因子：
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通讯作者：
M. Giese
中科院分区：
文献类型：
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作者：
Dominik M. Endres;H. Neumann;M. Kolesnik;M. Giese
我们调查了安全专家和天真的观察员在观察大型场景时，通常在足球比赛期间的体育场看台上遇到的危险事件的视觉搜索的差异。我们的主要技术目标是减少检测和识别此类事件所需的计算工作量。为了克服与真实的镜头相关的稀缺性和法律的问题，我们设计了一种新的算法，用于合成具有良好控制的统计特性的人群场景。我们的特征的显着性和专家知识的相对重要性，为安全专家和天真的观察员生成正确的检测和视觉搜索策略。我们发现，在这个搜索任务的最初几秒钟，专家和天真的观察者以类似的方式看待场景，但专家看到的更多。我们比较了显着性和事件分类的理论模型的结果。我们表明，识别模型可以提供合理的分类/检测性能，即使在实时约束下运行。当不考虑实时操作时，可以通过允许模型增长来进一步提高性能。（6页）
We investigated differences in visual search of dangerous events between security experts and naive observers during the observation of large scenes, typically encountered on the grandstand of stadiums during soccer matches. Our main technical objective was the reduction of computational effort required for the detection and recognition of such events. To overcome the scarcity and legal issues associated with real footage, we designed a new algorithm for the synthesis of crowd scenes with well-controlled statistical properties. We characterize the relative importance of saliency and expert knowledge for the generation of correct detections and the visual search strategies for both security experts and naive observers. We found that during the first few seconds of this search task, experts and naive observers look at the scenes in a similar fashion, but experts see more. We compare the results with theoretical models for saliency and event classification. We show that the recognition model can deliver reasonable classification/detection performance even when operating under real-time constraints. When real-time operation is not a concern, performance can be improved further by allowing the model to grow. (6 pages)