跟踪人员并识别他们的活动

Conference on Computer Vision and Pattern Recognition Workshops. IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Workshops Pub Date : 2005-06-20 DOI:10.1109/CVPR.2005.353

Deva Ramanan, D. Forsyth, Andrew Zisserman

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引用次数: 20

摘要

提出了一种自动跟踪和活动识别系统。我们进行人员跟踪的基本方法是为视频中的人建立一个外观模型。视频演示了我们使用程式化姿势检测器的方法。我们的系统从这些稀疏的程式化检测中建立肢体外观模型。然后，我们的算法重新处理视频，使用学习到的外观模型来寻找不受限制配置的人。我们可以使用跟踪器来恢复3D配置和活动标签。我们假设我们有一个动作捕捉库，其中3D姿势已被标记为离线活动描述。

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Tracking People and Recognizing Their Activities

We present a system for automatic people tracking and activity recognition. Our basic approach to people-tracking is to build an appearance model for the person in the video. The video illustrates our method of using a stylized-pose detector. Our system builds a model of limb appearance from those sparse stylized detections. Our algorithm then reprocesses the video, using the learned appearance models to find people in unrestricted configuration. We can use our tracker to recover 3D configurations and activity labels. We assume we have a motion capture library where the 3D poses have been labeled offline with activity descriptions.

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Conference on Computer Vision and Pattern Recognition Workshops. IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Workshops

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