2026-04-17T21:23:36Zhttps://recercat.cat/oai/request

oai:recercat.cat:2117/262702026-01-30T08:18:27Zcom_2072_1033col_2072_452950

Recognizing point clouds using conditional random fields Husain, Syed Farzad Dellen, Babette Torras, Carme Institut de Robòtica i Informàtica Industrial Universitat Politècnica de Catalunya. ROBiri - Grup de Robòtica de l'IRI Àrees temàtiques de la UPC::Informàtica::Robòtica computer vision object detection object recognition. Classificació INSPEC::Pattern recognition Detecting objects in cluttered scenes is a necessary step for many robotic tasks and facilitates the interaction of the robot with its environment. Because of the availability of efficient 3D sensing devices as the Kinect, methods for the recognition of objects in 3D point clouds have gained importance during the last years. In this paper, we propose a new supervised learning approach for the recognition of objects from 3D point clouds using Conditional Random Fields, a type of discriminative, undirected probabilistic graphical model. The various features and contextual relations of the objects are described by the potential functions in the graph. Our method allows for learning and inference from unorganized point clouds of arbitrary sizes and shows significant benefit in terms of computational speed during prediction when compared to a state-of-the-art approach based on constrained optimization. Peer Reviewed Postprint (author’s final draft) 2014 Conference report Husain, S.; Dellen, B.; Torras, C. Recognizing point clouds using conditional random fields. A: International Conference on Pattern Recognition. "Proceedings of the 22nd International Conference on Pattern Recognition". Stockhom: Institute of Electrical and Electronics Engineers (IEEE), 2014, p. 4257-4262. https://hdl.handle.net/2117/26270 10.1109/ICPR.2014.730 eng http://dx.doi.org/10.1109/ICPR.2014.730 201150E088 - CINNOVA info:eu-repo/grantAgreement/EC/FP7/269959/EU/Intelligent observation and execution of Actions and manipulations/INTELLACT http://creativecommons.org/licenses/by-nc-nd/3.0/es/ Open Access Attribution-NonCommercial-NoDerivs 3.0 Spain 6 p. application/pdf Institute of Electrical and Electronics Engineers (IEEE)