Fingertip detection for virtual keyboard based on camera

Hagara, Miroslav; Pucik, Jozef

doi:10.1109/radioelek.2013.6530945

Cited by 14 publications

(7 citation statements)

References 6 publications

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“…This type of virtual keyboard come in two popular types. The first type generally adopt a camera to recognize keystrokes by tracking finger movements or position through optical image data and gesture recognition algorithms [3]- [9]. The other type is the laser-based virtual keyboards [10]- [13] that mostly utilizing Infrared (IR) light and a camera to detect the movement and position of the fingers on a laser-projected virtual keyboard.…”

Section: A Vision-based Virtual Keyboardsmentioning

confidence: 99%

Wireless IoT Motion-Recognition Rings and a Paper Keyboard

et al. 2019

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In this paper, we present a new scheme for implementing virtual keyboards, which uses only two to four motion-recognition rings per hand and a two-dimensional keyboard template (e.g., an A4 size paper with printed key positions). It has the benefit of portability, customizability, and low-cost when compared with existing approaches. Essentially, we have shown that wearing two wireless IoT rings on the middle phalanges of two fingers of each hand, users can input the alphabetic characters into a computing device by typing on a flat paper on a desk, and potentially in mid-air. We have demonstrated that two rings are sufficient in capturing the gestures and motions of all fingers in a typing hand for keystrokes recognition. A single wireless IoT ring, which weighs 7.8 grams, consists of a Bluetooth low energy (BLE) unit, a micro inertial measurement unit (mIMU), and a cell battery. The 3-axes attitude angles and the Z-axis acceleration of each ring are adopted as the features for keystroke recognition. The overall keystroke recognition accuracy rate can reach as high as 94.8% when two IoT rings are worn by a user on each hand; this accuracy rate increases to 98.6%, when four rings are worn on each typing hand. INDEX TERMS Wearable sensors, wireless IoT ring, keystroke recognition, virtual keyboard, micro IMU.

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Section: A Vision-based Virtual Keyboardsmentioning

confidence: 99%

Wireless IoT Motion-Recognition Rings and a Paper Keyboard

et al. 2019

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“…Hand landmarks localization is performed in many gesture recognition systems, but usually it is limited to detecting fingertips of extended digits [6,14,17,25,45,54,57], as well as finding the wrist [11,32] and palm region [6,47,51]. This is certainly helpful for estimating a hand pose, when combined with the analysis of some shape features extracted from the hand silhouette or contour.…”

Section: Overview Of Vision-based Gesture Recognitionmentioning

confidence: 99%

“…Seldom has it been attempted to detect other landmarks associated with particular knuckles [45,51]. Existing approaches may be categorized into those that exploit (i) template matching [17,25,39,45], (ii) distance transform [6,30] and (iii) contour analysis [9,14,42,54].…”

Section: Hand Landmarks Detectionmentioning

confidence: 99%

“…The method exploits a multi-scale space to analyze the local curvatures of the contour, which makes it possible to detect the fingertips and digit bases located at the contour. The curvatures are also extracted from the mutual relations between the contour pixels and used to detect the fingertips in the virtual keyboard interface developed by Hagara and Pucik [14].…”

Section: Hand Landmarks Detectionmentioning

confidence: 99%

“…Introduction of the Kinect sensor has greatly improved the capacities of gesture recognition [29-31, 42, 52], however in order to increase the accessibility of touchless interfaces, more effective solutions based on computer vision would help in taking advantage of large popularity and low price inherent to standard 2D cameras. The vision-based systems [6,8,14,17,25,32,37,45,47,49,51,54,56,57,59] still do not allow for recognizing the gestures with sufficient accuracy, which brings the need for developing new image analysis algorithms for gesture recognition. One of the major problems here, addressed in this paper, is concerned with detecting and localizing hand landmarks, such as fingertips, joints, or phalanges.…”

Section: Introductionmentioning

confidence: 99%

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Hand landmarks detection and localization in color images

Grzejszczak

Kawulok

Gałuszka

2015

Multimed Tools Appl

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This paper introduces a new method for detecting and localizing hand landmarks in 2D color images. Location of the hand landmarks is an important source of information for recognizing hand gestures, effectively exploited in a number of recent methods which operate from the depth maps. However, this problem has not yet been satisfactorily solved for 2D color images. Here, we propose to analyze the skin-presence masks, as well as the directional image of a hand using the distance transform and template matching. This makes it possible to detect the landmarks located both at the contour and inside the hand masks. Moreover, we performed an extensive experimental study to compare the proposed method with a number of state-of-the-art algorithms. The obtained quantitative and qualitative results clearly indicate that our approach outperforms other methods, which may help improve the existing gesture recognition systems.

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Design and Implementation of Non Touch Enabled Password System

Varia

Modi

2016

Advances in Intelligent Systems and Computing

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Fingertip detection for virtual keyboard based on camera

Cited by 14 publications

References 6 publications

Wireless IoT Motion-Recognition Rings and a Paper Keyboard

Wireless IoT Motion-Recognition Rings and a Paper Keyboard

Hand landmarks detection and localization in color images

Design and Implementation of Non Touch Enabled Password System

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