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Robot awareness of human actions is an essential research problem in robotics with many important real-world applications, including human-robot collaboration and teaming. Over the past few years, depth sensors have become a standard device widely used by intelligent robots for 3D perception, which can also offer human skeletal data in 3D space. Several methods based on skeletal data were designed...
Currently, robot learning of human activities is mainly studied in two largely disconnected domains: high level semantics understanding in human activity recognition, and low level motion trajectory reproduction in robot imitation learning. The critical problem of human activity unified learning (HAUL) was not well studied in previous work. One important challenge is the lack of a representation that...
We present an algorithm for curve skeleton extraction via Laplacian-based contraction. Our algorithm can be applied to surfaces with boundaries, polygon soups, and point clouds. We develop a contraction operation that is designed to work on generalized discrete geometry data, particularly point clouds, via local Delaunay triangulation and topological thinning. Our approach is robust to noise and can...
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