PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Detecting Human Patterns in Laser Range Data
Theo Varvadoukas, Ioannis Giotis and Stasinos Konstantopoulos
In: 20th European Conference on Artificial Intelligence, 27-31 Aug 2012, Montpellier, France.

Abstract

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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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:User Modelling for Computer Human Interaction
Theory & Algorithms
ID Code:9585
Deposited By:Stasinos Konstantopoulos
Deposited On:13 October 2012