Fornas, DavidSanz, Pedro J.Porta, Josep M.Thomas, Federico2022-02-032022-02-032016Fornas, D., Sanz, P.J., Porta, J.M., Thomas F. Improving local symmetry estimations in RGB-D images by fitting superquadrics. En Actas de las XXXVII Jornadas de Automática. 7, 8 y 9 de septiembre de 2016, Madrid (pp. 162-168). DOI capítulo: https://doi.org/10.17979/spudc.9788497498081.0162 DOI libro: https://doi.org/10.17979/spudc.9788497498081978-84-617-4298-1 (UCM)978-84-9749-808-1 (UDC electrónico)http://hdl.handle.net/2183/29569[Abstract] Real-time manipulation tasks rely on finding good candidates for apprehension points which, in turn, usually requires the computation of local symmetries. When RGB-D images are used as input information, these local symmetries can be deduced from segmenting these images and computing geometric moments for each cluster of points. This approach gives a rough approximation because it does not take into account that the considered points lie on a surface. In this paper, to improve the quality of the symmetry estimations, we propose a simple refinement process that takes as input the estimation obtained using moments and then fits a superquadric to the considered set of points. We evaluate our approach on data collected using a Microsoft's Kinect 2 sensor. The obtained experimental results demonstrate the efficacy of the proposed approach.engAtribución-NoComercial-CompartirIgual 4.0 Internacionalhttps://creativecommons.org/licenses/by-nc-sa/4.0/deed.esSymmetry detectionPoint cloudsObject segmentationSuperquadricsKinect sensorconference outputopen access10.17979/spudc.9788497498081.0162