Keypoint-Less, Heuristic Application of Local 3D Descriptors

[1] Heuros 3D object recognition system. https://bitbucket.org/rrgwut/heuros. Accessed: 04-05-2015.Search in Google Scholar

[2] Aldoma, A., et al. CAD-model recognition and 6DOF pose estimation using 3D cues. In IEEE International Conference on Computer Vision Workshops, ICCV 2011 Workshops, Barcelona, Spain, November 6-13, 2011, 585–592. 2011.10.1109/ICCVW.2011.6130296Search in Google Scholar

[3] Alexandre, L. A. 3D descriptors for object and category recognition: a comparative evaluation. In Workshop on Color-Depth Camera Fusion in Robotics at the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Vilamoura, Portugal, 2012.Search in Google Scholar

[4] Alexandre, L. A. Set distance functions for 3D object recognition. In 18th Iberoamerican Congress on Pattern Recognition, volume LNCS 8258 of Lecture Notes in Computer Science, 57–64. Springer, Havana, Cuba, 2013.10.1007/978-3-642-41822-8_8Search in Google Scholar

[5] Cupec, R., et al. Detection of planar surfaces based on ransac and lad plane fitting. In Petrovic, I., Lilienthal, A. J., editors, ECMR, 37–42. KoREMA, 2009.Search in Google Scholar

[6] Farid, R. Region-Growing Planar Segmentation for Robot Action Planning, 179–191. Springer International Publishing, Cham, 2015.10.1007/978-3-319-26350-2_16Search in Google Scholar

[7] Filipe, S., Alexandre, L. A. A comparative evaluation of 3d keypoint detectors in a rgb-d object dataset. In 2014 International Conference on Computer Vision Theory and Applications (VISAPP). 2014.Search in Google Scholar

[8] Filipe, S., Itti, L., Alexandre, L. A. BIK-BUS: Biologically motivated 3D keypoint based on bottom-up saliency. IEEE Transactions on Image Processing, 24(1):163–175, 2015.Search in Google Scholar

[9] Ghorpade, V. K., et al. Performance evaluation of 3d keypoint detectors for time-of-fight depth data. In 2016 14th International Conference on Control, Automation, Robotics and Vision (ICARCV), 1–6. 2016.10.1109/ICARCV.2016.7838686Search in Google Scholar

[10] Harasymowicz-Boggio, B., Chechliński, L., Siemiatkowska, B. Nature-inspired, parallel object recognition. In Szewczyk, R., Zieliński, C., Kaliczyńska, M., editors, Progress in Automation, Robotics and Measuring Techniques. Control and Automation. Advances in Intelligent Systems and Computing vol. 350. Springer, 2015.10.1007/978-3-319-15796-2_6Search in Google Scholar

[11] Harasymowicz-Boggio, B., Chechliński, u., Siemiatkowska, B. Significance of features in object recognition using depth sensors. Optica Applicata, 45(4):559–571, 2015.10.1007/978-3-319-02294-9_71Search in Google Scholar

[12] Holz, D., et al. Robot soccer world cup xv. chapter Real-time Plane Segmentation Using RGB-D Cameras, 306–317. Springer-Verlag, Berlin, Heidelberg, 2012.10.1007/978-3-642-32060-6_26Search in Google Scholar

[13] Izadi, S., et al. Kinectfusion: real-time 3D reconstruction and interaction using a moving depth camera. In Proceedings of the 24th annual ACM symposium on User interface software and technology, UIST ‘11, 559–568. ACM, New York, NY, USA, 2011.10.1145/2047196.2047270Search in Google Scholar

[14] Kalogerakis, E., Hertzmann, A., Singh, K. Learning 3D mesh segmentation and labeling. ACM Trans. Graph., 29(4).10.1145/1778765.1778839Search in Google Scholar

[15] Lai, K., Bo, L., Fox, D. Unsupervised feature learning for 3D scene labeling. In IEEE International Conference on on Robotics and Automation. 2014.10.1109/ICRA.2014.6907298Search in Google Scholar

[16] Nathan Silberman, P. K., Derek Hoiem, Fergus, R. Indoor segmentation and support inference from RGBD images. In ECCV. 2012.10.1007/978-3-642-33715-4_54Search in Google Scholar

[17] Neves, A. J. R., et al. Object detection based on plane segmentation and features matching for a service robot. International Journal of Computer, Electrical, Automation, Control and Information Engineering, 10(4):745 – 752, 2016.Search in Google Scholar

[18] Osada, R., et al. Shape distributions. ACM Transactions on Graphics, 21(4):807–832, 2002.10.1145/571647.571648Search in Google Scholar

[19] Quigley, M., et al. Ros: an open-source robot operating system. In ICRA Workshop on Open Source Software. 2009.Search in Google Scholar

[20] Ren, X., Bo, L., Fox, D. RGB-D scene labeling: Features and algorithms. In IEEE International Conference on Computer Vision and Pattern Recognition, 2759–2766. 2012.Search in Google Scholar

[21] Rusu, R. B., Blodow, N., Beetz, M. Fast point feature histograms (FPFH) for 3D registration. In in In Proceedings of the International Conference on Robotics and Automation (ICRA. 2009.10.1109/ROBOT.2009.5152473Search in Google Scholar

[22] Rusu, R. B., Cousins, S. 3d is here: Point cloud library (pcl). In International Conference on Robotics and Automation. Shanghai, China, 2011.10.1109/ICRA.2011.5980567Search in Google Scholar

[23] Rusu, R. B., et al. Learning Informative Point Classes for the Acquisition of Object Model Maps. In Proceedings of the 10th International Conference on Control, Automation, Robotics and Vision (ICARCV), Hanoi, Vietnam, December 17-20. 2008.10.1109/ICARCV.2008.4795593Search in Google Scholar

[24] Rusu, R. B., et al. Close-range scene segmentation and reconstruction of 3d point cloud maps for mobile manipulation in domestic environments. In 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, 1–6. 2009.10.1109/IROS.2009.5354683Search in Google Scholar

[25] Rusu, R. B., et al. Detecting and segmenting objects for mobile manipulation. In Proceedings of IEEE Workshop on Search in 3D and Video (S3DV), held in conjunction with the 12th IEEE International Conference on Computer Vision (ICCV). Kyoto, Japan, 2009.Search in Google Scholar

[26] Rusu, R. B., et al. Fast 3d recognition and pose using the viewpoint feature histogram. In Proceedings of the 23rd IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Taipei, Taiwan, 2010.10.1109/IROS.2010.5651280Search in Google Scholar

[27] Song, S., Xiao, J. Deep sliding shapes for amodal 3d object detection in RGB-D images. CoRR, abs/1511.02300, 2015.Search in Google Scholar