Novel seed selection for multiple objects detection and tracking
Novel seed selection for multiple objects detection and tracking
复制标题
用于多个对象检测和跟踪的新颖种子选择
DOI：
10.1109/icpr.2004.1334366
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发表时间：
2004
期刊：
影响因子：
--
通讯作者：
C. Ngo
中科院分区：
文献类型：
--
作者：
Zailiang Pan;C. Ngo
提出了一种统一的多运动目标初始化、检测和跟踪方法。目标初始化通过新颖的种子选择来实现，该种子选择根据跟踪质量自适应地激活，以选择沿时间方向的最佳可能帧用于目标检测。然后使用EM算法对选定帧中的多个目标进行稳健分割和检测。每个检测到的目标用基于外观的模型来表示，并采用均值漂移跟踪过程来快速有效地跟踪目标目标。
This paper proposes a unified approach for initializing, detecting and tracking of multiple moving objects. Object initialization is achieved through novel seed selection which is adaptively activated, depending on the quality of tracking, to select the best possible frames along the temporal direction for object detection. EM algorithm is then employed to robustly segment and detect multiple objects in a selected frame. Each detected object is represented by an appearance-based model and mean shift tracking procedure is adopted to rapidly and effectively track the target objects.