Mid-air Authentication Gestures: An Exploration of Authentication Based on Palm and Finger Motions

ABSTRACT

Authentication based on touch-less mid-air gestures would benefit a multitude of ubicomp applications, which are used in clean environments (e.g., medical environments or clean rooms). In order to explore the potential of mid-air gestures for novel authentication approaches, we performed a series of studies and design experiments. First, we collected data from more then 200 users during a three-day science event organised within a shopping mall. This data was used to investigate capabilities of the Leap Motion sensor and to formulate an initial design problem. The design problem, as well as the design of mid-air gestures for authentication purposes, were iterated in subsequent design activities. In a final study with 13 participants, we evaluated two mid-air gestures for authentication purposes in different situations, including different body positions. Our results highlight a need for different mid-air gestures for differing situations and carefully chosen constraints for mid-air gestures.

References

1. M. Bashir, G. Scharfenberg, and J. Kempf. Person authentication by handwriting in air using a biometric smart pen device. In Proc. of BIOSIG 2011, 2011.
2. F. Coleca1, T. Martinetz, and E. Barth. Gesture interfaces with depth sensors. In M. Grzegorzek et al., editors, Time-of-Flight and Depth Imaging, volume 8200 of Springer Lecuture Notes on Computer Science, pages 207--227. 2013.
3. A. De Luca, M. Denzel, and H. Hussmann. Look into my eyes!: Can you guess my password? In Proc. of the 5th Symposium on Usable Privacy and Security, pages 7:1--7:12, New York, NY, USA, 2009. ACM.
4. A. De Luca, A. Hang, F. Brudy, C. Lindner, and H. Hussmann. Touch me once and i know it's you!: Implicit authentication based on touch screen patterns. In Proc. of CHI '12, pages 987--996, New York, NY, USA, 2012. ACM.
5. P. Dourish. Where the Action is: The Foundations of Embodied Interaction. A Bradford book. Bradford Books, 2004.
6. H. Feng and C. C. Wah. Online signature verification using a new extreme points warping technique. Pattern Recogn. Lett., 24(16):2943--2951, Dec. 2003.
7. S. Fong, Y. Zhuang, I. Fister, and I. F. Jr. A biometric authentication model using hand gesture images. Biomedical Engineering Online, 12(111), 2013.
8. T. Giorgino. Computing and visualizing dynamic time warping alignments in r: The dtw package. Journal of Statistical Software, 31(7):1--24, 8 2009.
9. J. Guerra-Casanova, C. Sanchez-Avila, G. Bailador, and A. de Santos Sierra. Authentication in mobile devices through hand gesture recognition. International Journal on Information Security, 11(2):65--83, 2012.
10. J. Guna, E. Stojmenova, A. Lugmayr, I. Humar, and M. Pogacnik. User identification approach based on simple gestures. In Proc. of SAME, pages 39--48, 2012.
11. M. Hamissi and K. Faez. Real-time hand gesture recognition based on the depth map for human robot interaction. International Journal of Electrical and Computer Engineering (IJECE), 3(6):770--778, 2013.
12. K. Karthik, K. Varalakshmi, and S. Ravi. A file authentication system using hand gesture passcodes. International Journal of Emerging Technologies in Computational and Applied Sciences (IJETCAS), 13(174):394--401, 2013.
13. W. Kasprzak, A. Wilkowski, and K. Czapnik. Hand gesture recognition based on free-form contours and probabilistic inference. International Journal of Applied Mathematics and Computational Sciences, 22(2):437--448, 2012.
14. S. Kavanagh. Facilitating natural user interfaces through freehand gesture recognition. In Proc. of CHI '12, New York, NY, USA, 2012. ACM.
15. K. Kosic, B. Arzensek, A. Kuhar, and M. Vogrincic. Towards new user interfaces based on gesture and sound identification. In Proc. of SQAMIA, pages 45--53, 2013.
16. J. Liu, Z. Wang, L. Zhong, et al. uWave: Accelerometer-based personalized gesture recognition and its applications. In Proc. of PerCom'09, 2009.
17. S. Mitra and T. Acharya. Gesture recognition: A survey. IEEE Transactions on Systems, Man, and Cybernetics - PartC: Applications and Reviews, 37(3):311--324, 2007.
18. D. L. Nelson, V. S. Reed, and J. R. Walling. Pictorial superiority effect. Journal of Experimental Psychology: Human Learning and Memory, 2(5), 1976.
19. O. Nieto and D. Sasha. Hand gesture recognition in mobile devices: Enhancing the musical experience. In Proc. of CMMR'13, 2013.
20. F. Parvini and C. Shahabi. An algorithmic approach for static and dynamic gesture recognition utilising mechanical and biomechanical characteristics. International Journal on Bioinformatics Research and Applications, 3(1):4--23, 2012.
21. L. Potter, J. Araullo, and L. Carter. The leap motion controller: a view on sign language. In Proc. of OzHCI'13, pages 175--178, 2013.
22. A. Ramamoorthy, N. Vaswani, S. Chaudhury, and S. Banerjee. Recognition of dynamic hand gestures. Pattern Recognition, 36:2069--2081, 2003.
23. S. Reiflinger, F. Wallhoff, M. Ablassmeier, T. Poitschke, and G. Rigoll. Static and dynamic hand-gesture recognition for augmented reality applications. In J. Jacko, editor, Proc. of HCII 2007, volume 4552 of Springer Lecture Notes on Computer Science, pages 728--737, 2007.
24. Z. Ren, J. Yuan, and Z. Zong. Robust hand gesture recognition based on finger- earth mover's distance with a commodity depth camera. In Proc. of ACM Multimedia 2011, pages 1093--1096, 2011.
25. K. Sabir, C. Stolte, B. Tabor, and S. O'Donoghue. The molecular control toolkit: Controlling 3d molecular graphics via gesture and voice. In Proc. of the IEEE Symposium on Biological Data Visualisation 2013, pages 49--56, 2013.
26. N. Sae-Bae, K. Ahmed, K. Isbister, and N. Memon. Biometric-rich gestures: A novel approach to authentication on multi-touch devices. In Proc. of CHI '12, pages 977--986, New York, NY, USA, 2012. ACM.
27. D. A. Schöon. Designing as reflective conversation with the materials of a design situation. Knowledge-Based Systems, 5(1):3--14, 1992.
28. R. Shadmehr and T. Brashers-Krug. Functional stages in the formation of human long term motor memory. Journal of Neuroscience, 17(1):409--419, Jan. 1997.
29. J. Tian, C. Qu, W. Xu, and S. Wang. Kinwrite: Handwriting-based authentication using kinect. In Proc. of the 20th Annual Network & Distributed System Security Symposium, 2013.
30. S. Vikram, L. Li, and S. Russel. Writing and sketching in the air, recognizing and controlling on the fly. In Extended Abstracts on Human Factors in Computing Systems CHI EA '13, pages 1179--1184, 2013.
31. Y. Yao and C.-T. Li. Real-time hand gesture recognition for uncontrolled environments using adaptive SURF tracking and hidden conditional random fields. In Proc. of ISVC'13, Springer, pages 542--551, 2013.
32. M. Ye et al. A survey on human motion analysis from depth data. In Time-of-Flight and Depth Imaging. Sensors, Algorithms, and Applications, volume 8200 of Springer, pages 149--187. 2013.
33. Y. Yin and R. Davis. Gesture Spotting and Recognition Using Salience Detection and Concatenated Hidden Markov Models. In Proc. of ICMI'13, pages 489--494, 2013.

Index Terms

• Human-centered computing

  • Human computer interaction (HCI)