Luis Almeida, Paulo Menezes, Jorge Dias


Vergence ability is an important visual behavior observed on living creatures when they use vision to interact with the environment. The notion of active observer is equally useful for robotic vision systems on tasks like object tracking, fixation and 3D environment structure recovery. Humanoid robotics are a potential playground for such behaviors. This paper describes the implementation of a real time binocular vergence behavior using cepstral filtering to estimate stereo disparities. By implementing the cepstral filter on a graphics processing unit (GPU) using Compute Unified Device Architecture (CUDA) we demonstrate that robust parallel algorithms that used to require dedicated hardware are now available on common computers. The cepstral filtering algorithm speed up is more than sixteen times than on a current CPU. The overall system is implemented in the binocular vision system IMPEP (IMPEP Integrated Multimodal Perception Experimental Platform) to illustrate the system performance experimentally.


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Paper Citation

in Harvard Style

Almeida L., Menezes P. and Dias J. (2011). STEREO VISION HEAD VERGENCE USING GPU CEPSTRAL FILTERING . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2011) ISBN 978-989-8425-47-8, pages 665-670. DOI: 10.5220/0003319406650670

in EndNote Style

JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2011)
SN - 978-989-8425-47-8
AU - Almeida L.
AU - Menezes P.
AU - Dias J.
PY - 2011
SP - 665
EP - 670
DO - 10.5220/0003319406650670

in Bibtex Style

author={Luis Almeida and Paulo Menezes and Jorge Dias},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2011)},