IEEE Trans Cybern. 2015 Jan;45(1):89-102. doi: 10.1109/TCYB.2014.2320493. Epub 2014 May 20.
In this paper, we study a novel hierarchical background model for intelligent video surveillance with the pan-tilt-zoom (PTZ) camera, and give rise to an integrated system consisting of three key components: background modeling, observed frame registration, and object tracking. First, we build the hierarchical background model by separating the full range of continuous focal lengths of a PTZ camera into several discrete levels and then partitioning the wide scene at each level into many partial fixed scenes. In this way, the wide scenes captured by a PTZ camera through rotation and zoom are represented by a hierarchical collection of partial fixed scenes. A new robust feature is presented for background modeling of each partial scene. Second, we locate the partial scenes corresponding to the observed frame in the hierarchical background model. Frame registration is then achieved by feature descriptor matching via fast approximate nearest neighbor search. Afterwards, foreground objects can be detected using background subtraction. Last, we configure the hierarchical background model into a framework to facilitate existing object tracking algorithms under the PTZ camera. Foreground extraction is used to assist tracking an object of interest. The tracking outputs are fed back to the PTZ controller for adjusting the camera properly so as to maintain the tracked object in the image plane. We apply our system on several challenging scenarios and achieve promising results.
在本文中，我们研究了一种用于智能视频监控的新型分层背景模型，该模型结合了球机的平移-倾斜-变焦（PTZ）功能，提出了一个由三个关键组件组成的集成系统：背景建模、观测帧配准和目标跟踪。首先，我们通过将 PTZ 相机的连续焦距范围划分为几个离散的层次，并将每个层次的宽场景划分为多个局部固定场景，构建了分层背景模型。通过旋转和变焦拍摄的宽场景由分层的局部固定场景集合来表示。然后，我们为每个局部场景提出了一种新的鲁棒特征来进行背景建模。其次，我们在分层背景模型中定位与观测帧对应的局部场景。通过快速近似最近邻搜索进行特征描述符匹配，从而实现帧配准。然后，使用背景减法检测前景对象。最后，我们将分层背景模型配置为一个框架，以方便在 PTZ 相机下使用现有的目标跟踪算法。前景提取用于辅助跟踪感兴趣的目标。跟踪输出反馈给 PTZ 控制器，以适当调整相机，使跟踪的目标保持在图像平面内。我们在几个具有挑战性的场景中应用了我们的系统，并取得了令人鼓舞的结果。
