APSUBA - Active Perception for Scene Understanding and Behaviour Analysis (APSUBA): An application for Social Robotic
Project Type: General Research Project
Research Field: International Cooperation and Networking
Sponsors: CRUP
Time span: 01/2011-12/2012


Active Perception for Scene Understanding and Behaviour Analysis (APSUBA): An application for Social Robotic. Wiki.

The aim of the presented project is to develop an active perception system of the environment, acting as an agent inside a heterogeneous sensor network, for scene understanding and behaviour analysis. The proposed perception system is composed of two different mechanisms: an active visual perception system and a metric perception system acting inside a network of heterogeneous sensor such as 3D laser scanner, Inertial Measurement Unit (IMU) and camera. Both two systems will be calibrated. The sensorial fusion allows detecting the regions of interest using active vision (e.g. changes in the scene, human-robot interaction, human/robot motion, etc). Metric information will be used for later segmentation and 3D modelled stages. Moreover, data fusion will be applied for both heterogeneous sensor calibration and perception. Finally, the models will be used for scene recognition and behaviour understanding. In order to obtain the relevant elements in the scene, a perception-based grouping process will be employed, which is performed by a hierarchical irregular pyramid. Using the information given by the visual mechanism, the metric perception system will provide 3D information of the interest sector, through developing a multi-layer homography-based reconstruction approach. The segmentation in large datasets will be achieved using clusters provided by Gaussian Mixture Models (GMM). These segments will be modelled using high level geometric features (superquadric surfaces), which will be used for the last stage of the system: scene understanding and behaviour analysis using Bayesian rules.

The proposed project will provide contributions in different topics like mobile-structure sensor network, heterogeneous sensor calibration, localization, scene recognition, 3D reconstruction, active perception, sensorial fusion or human behaviour understanding. The results of this project are also interesting in other research fields (e.g. smart environment).

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