User identification approach based on simple gestures

Guna, Jože; Stojmenova, Emilija; Lugmayr, Artur; Humar, Iztok; Pogačnik, M.

doi:10.1007/s11042-013-1635-1

Cited by 7 publications

(10 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Human (hand) gesture recognition [17,14] has already been explored in many applications like sign language recognition [20], device [19] and software control [25], augmented reality application [23] and authentication [1,7,10]. We may distinguish instrumented sytems, which use trackable markers mounted to the fingers (e.g., infrared targets [23]) and non-instrumented systems relying on vision techniques only.…”

Section: Introductionmentioning

confidence: 99%

Mid-air Authentication Gestures

Aslan

Uhl

Meschtscherjakov

et al. 2014

Proceedings of the 16th International Conference on Multimodal Interaction

View full text Add to dashboard Cite

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.

show abstract

Section: Introductionmentioning

confidence: 99%

Mid-air Authentication Gestures

Aslan

Uhl

Meschtscherjakov

et al. 2014

Proceedings of the 16th International Conference on Multimodal Interaction

View full text Add to dashboard Cite

show abstract

“…Gestures as behavioral attributes for identification are less invasive than the biometric physical ones. Previous works identify users with in-air single-gesture of digits [111], implicit pick-up or shaking [32], and signatures [69]. In this work, user identification based on the Kinect with gesture pairs is proposed, showing in evaluation a significant improvement on accuracy.…”

Section: Contributionsmentioning

confidence: 99%

“…As a first step to investigate the relationship between the way of tooth brushing and cognitive disease, the work [49] identifies users based on toothbrushing information using an embedded accelerometer. Guna et al [32] propose an intuitive identification system that uses 'implicit' gestures, which include 'pick-up' and 'shaking' movement acquired by accelerometer in a Nintendo WiiMote remote controller. These loosely defined gestures are simple, non-invasive, user-friendly and for all users.…”

Section: Gesture-based Identification Approachesmentioning

confidence: 99%

“…In the reviewed literature, the identification problem is induced as a classification problem. For example, some works [32,106] apply the Dynamic Time Warping (DTW) algorithm, which is a traditional template matching approach. In [32], a "super-gesture" concept, which combines acceleration features of multiple gestures in only one gesture template per user, is proposed to increase the computational efficiency and temporal stability.…”

Section: Gesture-based Identification Approachesmentioning

confidence: 99%

“…For example, some works [32,106] apply the Dynamic Time Warping (DTW) algorithm, which is a traditional template matching approach. In [32], a "super-gesture" concept, which combines acceleration features of multiple gestures in only one gesture template per user, is proposed to increase the computational efficiency and temporal stability. The DTW algorithm is chosen because it has the inherent abilities to compare time series of different lengths and sample rates, and it is simple to implement.…”

Section: Gesture-based Identification Approachesmentioning

confidence: 99%

See 2 more Smart Citations