Fast and Robust Landmark Tracking in X-ray Locomotion Sequences Containing Severe Occlusions
Fast and Robust Landmark Tracking in X-ray Locomotion Sequences Containing Severe Occlusions
复制标题
包含严重遮挡的 X 射线运动序列中快速、稳健的地标跟踪
DOI：
10.2312/pe/vmv/vmv12/015-022
复制
发表时间：
2012
影响因子：
2.4
通讯作者：
Joachim Denzler
中科院分区：
文献类型：
--
作者：
Manuel Amthor;D. Haase;Joachim Denzler
对动物运动理解的最新进展已证明它是生物学、运动科学和机器人学许多领域的关键要素。为了分析行走的动物，采用了高速 X 射线摄像。为了对这些 X 射线序列进行生物学评估，必须在每个帧中定位解剖标志。然而，由于动物的运动，严重的遮挡使这项任务变得复杂，并且无法应用标准的跟踪方法。我们提出了一种鲁棒的跟踪方法，该方法基于将模板划分为子模板以克服遮挡的想法。与其他子模板方法的区别在于，我们允许对单个假设的融合进行软决策，这极大地有利于跟踪稳定性。此外，我们还展示了如何将解剖知识纳入跟踪过程以进一步提高性能。对真实数据集的实验表明，我们的方法取得的结果优于现有的稳健方法。
Recent advances in the understanding of animal locomotion have proven it to be a key element of many fields in biology, motion science, and robotics. For the analysis of walking animals, high-speed x-ray videography is employed. For a biological evaluation of these x-ray sequences, anatomical landmarks have to be located in each frame. However, due to the motion of the animals, severe occlusions complicate this task and standard tracking methods can not be applied. We present a robust tracking approach which is based on the idea of dividing a template into sub-templates to overcome occlusions. The difference to other sub-template approaches is that we allow soft decisions for the fusion of the single hypotheses, which greatly benefits tracking stability. Also, we show how anatomical knowledge can be included into the tracking process to further improve the performance. Experiments on real datasets show that our method achieves results superior to those of existing robust approaches.