We introduce a body-based identification system that leverages individual differences in body segment lengths and hand waving gesture patterns. The system identifies users based on a two-second hand waving gesture captured by a Microsoft Kinect. To evaluate our system, we collected 8640 gesture measurements from 75 participants through two lab studies and a field study. In the first lab study, we evaluated the feasibility of our concept and basic properties of features to narrow down the design space. In the second lab study, our system achieved a 1% equal error rate in user identification among seven registered users after two weeks following initial registration. We also found that our system was robust even when lower body segments could not be measured because of occlusions. In the field study, our system achieved 0.5 to 1.6% equal error rates, demonstrating that the system also works well in ecologically valid situations. Lastly, throughout the studies, our participants were positive about the system.
Wave to Me: User Identification Using Body Lengths and Natural Gestures, at CHI 2014
1. Wave to Me: User Identification Using
Body Lengths and Natural Gestures
Eiji Hayashi
Manuel Maas
Jason Hong
Human-Computer Interaction Institute
Carnegie Mellon University
32. Errors
False Acceptance Rate (FAR)
Accept others as a registered user
False Rejection Rate (FRR)
Reject a registered user as others
33. Errors
False Acceptance Rate (FAR)
Accept others as a registered user
False Rejection Rate (FRR)
Reject a registered user as others
Equal Error Rate (EER)
FAR = FRR = EER
34. Errors
False Acceptance Rate (FAR)
Accept others as a registered user
False Rejection Rate (FRR)
Reject a registered user as others
Equal Error Rate (EER)
FAR = FRR = EER
Accuracy = 1 – 2 x EER
48. Using Either Gesture or Lengths
Same day & posture
3 days later
Different Posture
Same day & posture
3 days later
Different Posture
Gesture Body Lengths
EER [%]
49. Using Either Gesture or Lengths
Same day & posture
3 days later
Different Posture
Same day & posture
3 days later
Different Posture
Gesture Body Lengths
EER [%]
2.1%
0.5%
50. Using Either Gesture or Lengths
Same day & posture
3 days later
Different Posture
Same day & posture
3 days later
Different Posture
Gesture Body Lengths
EER [%]
11.8%
19.8%
51. Using Either Gesture or Lengths
Same day & posture
3 days later
Different Posture
Same day & posture
3 days later
Different Posture
Gesture Body Lengths
EER [%]
10.0%
41.5%
52. Using Both Gesture and Lengths
3 days later
3 days later
Gesture Body Lengths
EER [%]
Both
3 days later (Standing)
3 days later (Sitting)
4.3%
6.2%
53. System
Lab Study 1 (Basic Evals)
Lab study 2 (Long-term Eval)
Field Study
62. System
Lab Study 1 (Basic Evals)
Lab study 2 (Long-term Eval)
Field Study
63. Does it Work at Homes?
• Collected data at participants’ living rooms
• Placed a Kinect on a TV
• Asked participant to behave as usual
– Stand where you feel reasonable
– Sit as you normally do in a living room
67. • Natural gestures + body lengths
• 2 seconds of hand waving gesture
Conclusion
Gesture
Body Lengths
Proposed Scheme
EER [%]
68. Wave to Me: User Identification Using
Body Lengths and Natural Gestures
Eiji Hayashi
ehayashi@cs.cmu.edu
www.cs.cmu.edu/~ehayashi/
Human-Computer Interaction Institute
Carnegie Mellon University