SERVICIO TERRITORIAL DE MEDIO AMBIENTE

This system is offered as a commodity component for HRI systems, with state of the art speed and robustness, and comparable performance to other systems at close range, but a larger usable interaction envelope. Source code including a ROS node is provided at https://github.com/ AutonomyLab/pointing_gesture. The commit hash for the version used to obtain the results in this paper is 7a4fe3a102c528c606cb3cac6e91cede8d54b80a.

Bibliography

[1] Cyberglove systems llc. http://www.cyberglovesystems.com/. Accessed: 2018-10-30. [2] Rıza Alp Güler, Natalia Neverova, and Iasonas Kokkinos. Densepose: Dense human pose

estimation in the wild. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pages 7297–7306, 2018.

[3] Tamara L. Berg, Alexander C. Berg, Jaety Edwards, and David A. Forsyth. Who’s in the picture. In L. K. Saul, Y. Weiss, and L. Bottou, editors, Advances in Neural Information Processing Systems (NIPS), pages 137–144. MIT Press, 2005.

[4] Zhe Cao, Gines Hidalgo, Tomas Simon, Shih-En Wei, and Yaser Sheikh. Openpose: realtime multi-person 2d pose estimation using part affinity fields. arXiv preprint arXiv:1812.08008, 2018.

[5] Akansel Cosgun, AJ Trevor, and Henrik I Christensen. Did you mean this object?: Detect- ing ambiguity in pointing gesture targets. In Human-Robot Interaction (HRI) workshop on Towards a Framework for Joint Action, Portland, OR, USA, pages 2–5. IEEE Press, 2015. [6] Alex Couture-Beil, Richard T Vaughan, and Greg Mori. Selecting and commanding indi-

vidual robots in a vision-based multi-robot system. In Proceedings of the 5th ACM/IEEE international conference on Human-robot interaction, pages 355–356. IEEE Press, 2010. [7] Laura Dipietro, Angelo M Sabatini, and Paolo Dario. A survey of glove-based systems and

their applications. In IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applica- tions and Reviews), volume 38, pages 461–482. IEEE, 2008.

[8] David Droeschel, Jörg Stückler, and Sven Behnke. Learning to interpret pointing gestures with a time-of-flight camera. In Human-Robot Interaction (HRI), 2011 6th ACM/IEEE Inter- national Conference on, pages 481–488. IEEE, 2011.

[9] Martin Ester, Hans-Peter Kriegel, Jörg Sander, Xiaowei Xu, et al. A density-based algorithm for discovering clusters in large spatial databases with noise. In Knowledge Discovery and Data Mining (KDD), volume 96, pages 226–231. AAAI Press, 1996.

[10] Mark Everingham, Luc Van Gool, Christopher KI Williams, John Winn, and Andrew Zisser- man. The pascal visual object classes (voc) challenge. In International Journal of Computer Vision (IJCV), volume 88, pages 303–338. Springer, 2010.

[11] John A Hartigan and Manchek A Wong. Algorithm as 136: A k-means clustering algorithm. In Journal of the Royal Statistical Society. Series C (Applied Statistics), volume 28, pages 100–108. JSTOR, 1979.

[12] Oliver Herbort and Wilfried Kunde. How to point and to interpret pointing gestures? instruc- tions can reduce pointer–observer misunderstandings. In Psychological Research, volume 82, pages 395–406. Springer, Mar 2018.

[13] Pan Jing and Guan Ye-Peng. Human-computer interaction using pointing gesture based on an adaptive virtual touch screen. In International Journal of Signal Processing, Image Processing and Pattern Recognition (IJSIP), volume 6, pages 81–91, 2013.

[14] R. Kehl and L. Van Gool. Real-time pointing gesture recognition for an immersive envi- ronment. In Sixth IEEE International Conference on Automatic Face and Gesture Recogni- tion(FG), pages 577–582. IEEE, May 2004.

[15] Yuhui Lai, Chen Wang, Yanan Li, Shuzhi Sam Ge, and Deqing Huang. 3d pointing gesture recognition for human-robot interaction. In Control and Decision Conference (CCDC), pages 4959–4964. IEEE, 2016.

[16] Brian Milligan, Greg Mori, and Richard Vaughan. Selecting and commanding groups of robots in a vision based multi-robot system (video - winner of best video prize). In Video Proceedings of the 6th ACM/IEEE International Conference on Human-Robot Interaction (HRI), Lausanne, Switzerland, March 2011. IEEE.

[17] Sushmita Mitra and Tinku Acharya. Gesture recognition: A survey. In IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), volume 37, pages 311– 324. IEEE, 2007.

[18] Arpit Mittal, Andrew Zisserman, and Philip HS Torr. Hand detection using multiple proposals. In British Machine Vision Conference (BMVC), pages 1–11. Citeseer, 2011.

[19] Sepehr MohaimenianPour. Robust real-time hands-and-face detection for human robot inter- action. Master’s thesis, Simon Fraser University, April 2018.

[20] Sepehr MohaimenianPour and Richard Vaughan. Hands and faces, fast: Mono-camera user detection robust enough to directly control a UAV in flight. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Madrid, Spain. IEEE, October 2018.

[21] Greg Mori, Caroline Pantofaru, Nisarg Kothari, Thomas Leung, George Toderici, Alexander Toshev, and Weilong Yang. Pose embeddings: A deep architecture for learning to match human poses. arXiv preprint arXiv:1507.00302, 2015.

[22] Kai Nickel and Rainer Stiefelhagen. Pointing gesture recognition based on 3d-tracking of face, hands and head orientation. In Proceedings of the 5th International Conference on Multimodal Interfaces (ICMI), ICMI ’03, pages 140–146, New York, NY, USA, 2003. ACM.

[23] Kai Nickel and Rainer Stiefelhagen. Real-time person tracking and pointing gesture recogni- tion for human-robot interaction. In International Workshop on Computer Vision in Human- Computer Interaction (HRI), pages 28–38. Springer, 2004.

[24] Kai Nickel and Rainer Stiefelhagen. Visual recognition of pointing gestures for human-robot interaction. In Image and Vision Computing, volume 25, pages 1875–1884. Elsevier, 2007.

[25] Payam Nikdel, Rakesh Shrestha, and Richard Vaughan. The hands-free push-cart: Au- tonomous following in front by predicting user trajectory around obstacles. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA). IEEE, May 2018. [26] Chang-Beom Park and Seong-Whan Lee. Real-time 3d pointing gesture recognition for mobile robots with cascade hmm and particle filter. In Image and Vision Computing, volume 29, pages 51–63. Elsevier, 2011.

[27] Maria Pateraki, Haris Baltzakis, and Panos Trahanias. Visual estimation of pointed targets for robot guidance via fusion of face pose and hand orientation. In Computer Vision and Image Understanding, volume 120, pages 1–13. Elsevier, 2014.

[28] Shokoofeh Pourmehr, Mani Monajjemi, Jens Wawerla, Richard Vaughan, and Greg Mori. A robust integrated system for selecting and commanding multiple mobile robots. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA). IEEE, May 2013. [29] David L Quam. Gesture recognition with a dataglove. In National Aerospace and Electronics Conference, 1990. NAECON 1990., Proceedings of the IEEE 1990 National, pages 755–760. IEEE, 1990.

[30] Siddharth S Rautaray and Anupam Agrawal. Vision based hand gesture recognition for hu- man computer interaction: a survey. In Artificial Intelligence Review, volume 43, pages 1–54. Springer, 2015.

[31] Joseph Redmon and Ali Farhadi. Yolo9000: Better, faster, stronger. arXiv preprint arXiv:1612.08242, 2016.

[32] Jan Richarz, Andrea Scheidig, Christian Martin, Steffen Müller, and Horst-Michael Gross. A monocular pointing pose estimator for gestural instruction of a mobile robot. In International Journal of Advanced Robotic Systems (IJARS), volume 4, page 17. SAGE Publications Sage UK: London, England, 2007.

[33] Dadhichi Shukla, Ozgur Erkent, and Justus Piater. Probabilistic detection of pointing direc- tions for human-robot interaction. In Digital Image Computing: Techniques and Applications (DICTA), 2015 International Conference on, pages 1–8. IEEE, 2015.

[34] Jesus Suarez and Robin R Murphy. Hand gesture recognition with depth images: A review. In Ro-man, 2012 IEEE, pages 411–417. IEEE, 2012.

[35] Alexander Toshev and Christian Szegedy. Deeppose: Human pose estimation via deep neural networks. In Proceedings of the IEEE conference on computer vision and pattern recognition, pages 1653–1660, 2014.

[36] Kohei Toyoda, Michinari Kono, and Jun Rekimoto. Post-data augmentation to improve deep pose estimation of extreme and wild motions. arXiv preprint arXiv:1902.04250, 2019. [37] Satoshi Ueno, Sei Naito, and Tsuhan Chen. An efficient method for human pointing estimation

for robot interaction. In Image Processing (ICIP), 2014 IEEE International Conference on, pages 1545–1549. IEEE, 2014.

[38] Hiroki Watanabe, Hitoshi Hongo, Mamoru Yasumoto, and Kazuhiko Yamamoto. Detection and estimation of omni-directional pointing gestures using multiple cameras. In Workshop on Machine Vision Application (MVA), pages 345–348. MVA, 2000.

[39] Andrew D Wilson and Aaron F Bobick. Parametric hidden markov models for gesture recogni- tion. In IEEE transactions on Pattern Analysis and Machine Intelligence (PAMI), volume 21, pages 884–900. IEEE, 1999.

[40] Christian Wittner, Boris Schauerte, and Rainer Stiefelhagen. What’s the point? frame-wise pointing gesture recognition with latent-dynamic conditional random fields. arXiv preprint arXiv:1510.05879, 2015.

[41] Lingkang Zhang and Richard Vaughan. Optimal robot selection by gaze direction in multi- human multi-robot interaction. In Proceedings of the IEEE International Conference on Intel- ligent Robots and Systems (IROS). IEEE, October 2016.