A combined vision-inertial fusion approach for 6-DoF object pose estimation

Juan Li; Ana M. Bernardos; Paula Tarrío; José R. Casar

doi:10.1117/12.2180574

14 February 2015 A combined vision-inertial fusion approach for 6-DoF object pose estimation

Juan Li, Ana M. Bernardos, Paula Tarrío, José R. Casar

Proceedings Volume 9445, Seventh International Conference on Machine Vision (ICMV 2014); 944518 (2015) https://doi.org/10.1117/12.2180574
Event: Seventh International Conference on Machine Vision (ICMV 2014), 2014, Milan, Italy

Abstract

The estimation of the 3D position and orientation of moving objects (‘pose’ estimation) is a critical process for many applications in robotics, computer vision or mobile services. Although major research efforts have been carried out to design accurate, fast and robust indoor pose estimation systems, it remains as an open challenge to provide a low-cost, easy to deploy and reliable solution. Addressing this issue, this paper describes a hybrid approach for 6 degrees of freedom (6-DoF) pose estimation that fuses acceleration data and stereo vision to overcome the respective weaknesses of single technology approaches. The system relies on COTS technologies (standard webcams, accelerometers) and printable colored markers. It uses a set of infrastructure cameras, located to have the object to be tracked visible most of the operation time; the target object has to include an embedded accelerometer and be tagged with a fiducial marker. This simple marker has been designed for easy detection and segmentation and it may be adapted to different service scenarios (in shape and colors). Experimental results show that the proposed system provides high accuracy, while satisfactorily dealing with the real-time constraints.

Citation Download Citation

Juan Li, Ana M. Bernardos, Paula Tarrío, and José R. Casar "A combined vision-inertial fusion approach for 6-DoF object pose estimation", Proc. SPIE 9445, Seventh International Conference on Machine Vision (ICMV 2014), 944518 (14 February 2015); https://doi.org/10.1117/12.2180574

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