Movies Fight Detection Dataset

Whereas the action recognition community has focused mostly on detecting simple actions like clapping, walking or jogging, the detection of fights or in general aggressive behaviors has been comparatively less studied. Such capability may be extremely useful in some video surveillance scenarios like in prisons, psychiatric or elderly centers or even in camera phones. After an analysis of previous approaches we test the well-known Bag-of-Words framework used for action recognition in the specific problem of fight detection, along with two of the best action descriptors currently available: STIP and MoSIFT. For the purpose of evaluation and to foster research on violence detection in video we introduce a new video database containing 1000 sequences divided in two groups: fights and non-fights. Experiments on this database and another one with fights from action movies show that fights can be detected with near 90% accuracy.

尽管动作识别领域主要聚焦于诸如鼓掌、行走或慢跑等简单动作的检测，然而对于斗殴或广义上的攻击性行为的识别研究相对较少。此类能力在监狱、精神卫生中心或甚至摄像头手机等视频监控场景中可能极为有用。在对先前方法进行分析的基础上，我们对用于动作识别的知名词袋模型框架在斗殴检测的特定问题中进行测试，并评估了目前可用的最佳动作描述符中的两种：STIP和MoSIFT。为了评估目的并促进视频暴力检测的研究，我们引入了一个包含1000个序列的新视频数据库，这些序列分为两组：斗殴和非斗殴。在此数据库以及另一个包含动作电影中斗殴片段的数据库上的实验表明，斗殴的检测准确率可接近90%。

搜集汇总

背景与挑战

背景概述

该数据集是一个用于视频中打斗检测研究的视频数据库，包含1000个序列，分为打斗和非打斗两类，旨在评估和促进暴力检测算法的发展。数据集应用于动作识别和视频监控场景，如监狱、精神病院或老年中心，通过实验验证打斗检测准确率可达近90%。