Detecting Human Patterns in Laser Range Data
نویسندگان
چکیده
In this paper we present a novel method for detecting humans from laser range scans, where the core idea is to treat neither individual frames, which hold so little information that the task is impossible, nor motion patterns, as is the case with tracking methods. Rather, we map short time series of planar scans to 3D objects with time as the depth dimension; we then cluster and classify these 3D objects using unsupervised and off-line training, circumventing the need for predefining and parametrizing motion models.
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