Human detection using oriented histograms of flow and appearance
Human detection using oriented histograms of flow and appearance
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DOI：
10.1007/11744047_33
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发表时间：
2006-01-01
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影响因子：
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通讯作者：
Schmid, Cordelia
中科院分区：
文献类型：
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作者：
Dalal, Navneet;Triggs, Bill;Schmid, Cordelia
由于被摄体、摄像机和背景的运动，以及姿势、外观、服装、光照和背景杂乱的变化，在电影和视频中检测人类是一个具有挑战性的问题。我们开发了一种检测器，用于在可能有运动摄像机和背景的视频中站立和运动的人，测试了几种不同的运动编码方案，并经验地表明，差分光流的定向直方图给出了最佳的整体性能。这些基于运动的描述符与定向渐变外观描述符的直方图相结合。所产生的探测器在几个数据库上进行了测试，其中包括从故事片中获取的具有挑战性的测试集，该测试集包含广泛的姿势、运动和背景变化，包括移动的摄像机和背景。我们在两个具有挑战性的测试集上验证了我们的结果，这些测试集包含4400多个人类样本。与最好的基于外观的检测器相比，该组合检测器将虚警率降低了10倍，例如，在我们的测试集1上，以8%的漏检率测试的每20,000个窗口的虚警率为I。
Detecting humans in films and videos is a challenging problem owing to the motion of the subjects, the camera and the background and to variations in pose, appearance, clothing, illumination and background clutter. We develop a detector for standing and moving people in videos with possibly moving cameras and backgrounds, testing several different motion coding schemes and showing empirically that orientated histograms of differential optical flow give the best overall performance. These motion-based descriptors are combined with our Histogram of Oriented Gradient appearance descriptors. The resulting detector is tested on several databases including a challenging test set taken from feature films and containing wide ranges of pose, motion and background variations, including moving cameras and backgrounds. We validate our results on two challenging test sets containing more than 4400 human examples. The combined detector reduces the false alarm rate by a factor of 10 relative to the best appearance-based detector, for example giving false alarm rates of I per 20,000 windows tested at 8% miss rate on our Test Set 1.