多媒体应用中基于卡尔曼滤波和人脸追踪的多人实时跟踪

V. Girondel, A. Caplier, L. Bonnaud
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引用次数: 14

摘要

我们提出了一种算法,可以在视频序列中同时跟踪多个人和他们的脸,即使他们在摄像机的视角中完全被遮挡。该算法基于对人脸及其面具的检测和跟踪。人脸定位使用基于颜色信息的皮肤检测和自适应阈值。为了处理遮挡,为每个人定义了一个卡尔曼滤波器,该滤波器允许预测人边界框、人脸边界框及其速度。在测量不完全的情况下(例如,在部分遮挡的情况下),进行部分卡尔曼滤波。实验结果表明了该方法的有效性。该算法允许实时处理。
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Real time tracking of multiple persons by Kalman filtering and face pursuit for multimedia applications
We present an algorithm that can track multiple persons and their faces simultaneously in a video sequence, even if they are completely occluded from the camera's point of view. The algorithm is based on the detection and tracking of person masks and their faces. Face localization uses skin detection based on color information with an adaptive thresholding. In order to handle occlusions, a Kalman filter is defined for each person that allows the prediction of the person bounding box, of the face bounding box and of its speed. In case of incomplete measurements (for instance, in case of partial occlusion), a partial Kalman filtering is done. Several results show the efficiency of this method. This algorithm allows real time processing.
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