André Morais

[1] F. Tombari and L. D. Stefano, “Hough Voting for 3D Object Recognition under Occlusion and Clutter,” IPSJ Transactions on Computer Vision and Applications, vol. 4, pp. 20–29,2012.

[2] D. Lowe, “Object Recognition fromLocal Scale-Invariant Features,” IEEE International Conference on Computer Vision, 1999.

[3] R. B. Rusu, “Semantic 3D Object Maps for Everyday Manipulation in Human Living Environments,”pp. 1–4, 2010.

[4] M. a. Fischler and R. C. Bolles, “Random Sample Consensus: A Paradigm for Model Fitting with,” Communications of the ACM, vol. 24, pp. 381–395, 1981.

[5] H. Bay, T. Tuytelaars, and L. Van Gool, “SURF: Speeded up robust features,” Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3951 LNCS, pp. 404–417, 2006.

[6] L. Qiang and L. Feng, “RGB-D sensor based mobile robot SLAM in indoor environment,” Control and Decision . . . , pp. 3848–3852, 2014.

[7] J. a. Batista, “Sistema de Reconhecimento de Objetos para Demonstrador de Condução Robótica Autónoma,” p. 60, 2011.

[8] N. Vaskevicius, K. Pathak, A. Ichim, and A. Birk, “The Jacobs Robotics approach to object recognition and localization in the context of the ICRA’11 Solutions in Perception

Challenge,” Proceedings - IEEE International Conference on Robotics and Automation, pp.

3475–3481, 2012.

[9] E. T. H. Zurich, “APPLIED REGISTRATION FOR ROBOTICS Methodology and Tools for ICP-like Algorithms,” no. 21159, 2013.

[10] W. Guo, T. Du, X. Zhu, and T. Hu, “Kinect-Based Real-Time Rgb-D Image Fusion Method,” ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. XXXIX-B3, no. September, pp. 275–279, 2012.

[11] J. Marcel, “Object Detection and Recognition with Microsoft Kinect,” 2012.