IROS 2007 : A Spatio-Temporal Probabilistic Model for Multi-Sensor Object

Bertrand Douillard, Dieter Fox, Fabio Ramos

Abstract:

This paper presents a general framework for multi-sensor object recognition through a discriminative probabilistic approach modelling spatial and temporal correlations.The algorithm is developed in the context of Conditional Random Fields (CRFs) trained with virtual evidence boosting.The resulting system is able to integrate arbitrary sensorinformation and incorporate features extracted from the data.The spatial relationships captured by are further integratedinto a smoothing algorithm to improve recognition over time.We demonstrate the benefits of modelling spatial and temporal relationships for the problem of detecting cars using laser and vision data in outdoor environments.

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