计算机视觉
人工智能
闭塞
跟踪(教育)
核(代数)
计算机科学
连贯性(哲学赌博策略)
数学
医学
心理学
教育学
统计
组合数学
心脏病学
作者
Jingyi Xiang,Holly Dinkel,Huijing Zhao,Naixiang Gao,Brian Coltin,Trey Smith,Timothy Bretl
出处
期刊:IEEE robotics and automation letters
日期:2023-10-01
卷期号:8 (10): 6179-6186
被引量:1
标识
DOI:10.1109/lra.2023.3303710
摘要
The TrackDLO algorithm estimates the shape of a Deformable Linear Object (DLO) under occlusion from a sequence of RGB-D images. TrackDLO is vision-only and runs in real-time. It requires no external state information from physics modeling, simulation, visual markers, or contact as input. The algorithm improves on previous approaches by addressing three common scenarios which cause tracking failure: tip occlusion, mid-section occlusion, and self-occlusion. This is achieved through the application of Motion Coherence Theory to impute the spatial velocity of occluded nodes, the use of the topological geodesic distance to track self-occluding DLOs, and the introduction of a non-Gaussian kernel that only penalizes lower-order spatial displacement derivatives to reflect DLO physics. Improved real-time DLO tracking under mid-section occlusion, tip occlusion,and self-occlusion is demonstrated experimentally. The source code and demonstration data are publicly released.
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