Gestensteuerung für Fahrzeugbordsysteme

Akyol, Suat; Canzler, Ulrich; Bengler, Klaus; Hahn, Wolfgang

doi:10.1007/978-3-642-59802-9_18

Cited by 3 publications

(4 citation statements)

References 8 publications

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“…Researchers that did conduct experimental evaluation of AGs have used 'wizard of oz' methods that ultimately have limited validity. Alpern and Minardo simulated a system similar to [1], compared it with a turnknob interface, and found that subjective feedback sided with the AG system [2].…”

Section: Air Gestures In the Vehiclementioning

confidence: 95%

“…Akyol et al designed a system that selectively mapped six static one-handed poses to either news or email functions depending on the current mode, and provided both visual and non-speech auditory feedback [1]. Rahman et al explored a similar system in which the driver controlled multimedia playback using absolute mapped directional swipes [13].…”

Section: Air Gestures In the Vehiclementioning

confidence: 99%

“…A number of researchers have explored different styles of in-vehicle AG interfaces without conducting evaluations [1,14,3]. Akyol et al designed a system that selectively mapped six static one-handed poses to either news or email functions depending on the current mode, and provided both visual and non-speech auditory feedback [1].…”

Section: Air Gestures In the Vehiclementioning

confidence: 99%

See 2 more Smart Citations

A Multimodal Air Gesture Interface for In Vehicle Menu Navigation

May

Gable

Walker

2014

Adjunct Proceedings of the 6th International Conference on Automotive User Interfaces and Interactive Vehicular Applications

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Section: Air Gestures In the Vehiclementioning

confidence: 95%

Section: Air Gestures In the Vehiclementioning

confidence: 99%

Section: Air Gestures In the Vehiclementioning

confidence: 99%

See 1 more Smart Citation

A Multimodal Air Gesture Interface for In Vehicle Menu Navigation

May

Gable

Walker

2014

Adjunct Proceedings of the 6th International Conference on Automotive User Interfaces and Interactive Vehicular Applications

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“…In (Akyol et al, 2000) a concept for gesture control of in-car systems is described. The system developed from BMW and the RWTH Aachen works with near infrared light and a modified CCD camera and a Maximum-Likelihood classification algorithm.…”

Section: Touchless Gestures For Automotive Applicationsmentioning

confidence: 99%

Contactless Interaction for Automotive Applications

Kopinski¹,

Geisler²,

Handmann³

2013

Mensch &Amp; Computer 2013 - Workshopband

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Touchless gestures are getting more and more popular since Microsoft introduced the Kinect. They are not only interesting for entertainment and games, but also advantageous for in-car applications, as the driver can keep the hand closer to the steering wheel and displays can be mounted closer to the line of visibility at positions normally not in the reach zone. Since the technology used in consumer electronics is generally not suitable for automotive applications an alternative approach including hard-and software aspects is presented in this paper. A second aspect is the identification of the driver with biometric methods. The base idea is to also work contactless and omit additional technology which drivers need to carry with them, but in many cases they don't or share it between different persons (like the key).

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Gesture recognition with a Time-Of-Flight camera

Kollorz

Penne

Hornegger

et al. 2008

IJISTA

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This paper presents a new approach for gesture classification using x-and y-projections of the image and optional depth features. The system uses a 3-D time-of-flight (TOF) sensor which has the big advantage of simplifying hand segmentation. For the presented system, a Photonic-Mixer-Device (PMD) camera with a resolution of 160 × 120 pixels and a frame rate of 15 frames per second is used. The goal of our system is to recognise 12 different static hand gestures. The x-and y-projections and the depth features of the captured image are good enough to use a simple nearest neighbour classifier, resulting in a fast classification. To evaluate the system, a set of 408 images is recorded, 12 gestures from 34 persons. With a 'Leave-One-Out' evaluation, the recognition rate of the system is 94.61 %, and classification time is about 30 ms on a standard PC.

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Gestensteuerung für Fahrzeugbordsysteme

Cited by 3 publications

References 8 publications

A Multimodal Air Gesture Interface for In Vehicle Menu Navigation

A Multimodal Air Gesture Interface for In Vehicle Menu Navigation

Contactless Interaction for Automotive Applications

Gesture recognition with a Time-Of-Flight camera

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