Bridging the Gap between Detection and Tracking for 3D Monocular Video-Based Motion Capture
Bridging the Gap between Detection and Tracking for 3D Monocular Video-Based Motion Capture
复制标题
弥合基于 3D 单目视频的运动捕捉的检测和跟踪之间的差距
DOI：
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发表时间：
2007
期刊：
影响因子：
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通讯作者：
P. Fua
中科院分区：
文献类型：
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作者：
A. Fossati;M. Dimitrijevic;V. Lepetit;P. Fua
我们结合了检测和跟踪技术，以实现稳健的3-D运动恢复的人从任何角度通过一个单一的和潜在的移动摄像机。我们依赖于检测关键姿势，这可以可靠地完成，使用运动模型在连续检测之间推断3D姿势，最后使用生成模型在整个序列中提炼它们。我们在人们在杂乱的背景下行走并使用移动摄像机拍摄的情况下演示了我们的方法，这排除了使用简单的背景减去技术的可能性。在这种情况下，容易发现的姿势是在每一步结束时，当人们的腿分开最远的时候出现的姿势。
We combine detection and tracking techniques to achieve robust 3-D motion recovery of people seen from arbitrary viewpoints by a single and potentially moving camera. We rely on detecting key postures, which can be done reliably, using a motion model to infer 3-D poses between consecutive detections, and finally refining them over the whole sequence using a generative model. We demonstrate our approach in the case of people walking against cluttered backgrounds and filmed using a moving camera, which precludes the use of simple background subtraction techniques. In this case, the easy-to-detect posture is the one that occurs at the end of each step when people have their legs furthest apart.