Organising Bodyformation of Modular Autonomous Robots Using Virtual Embryogenesis

Daushan, M.; Thenius, Ronald; Schmickl, Thomas

doi:10.1007/978-3-319-59972-4_6

Cited by 2 publications

(2 citation statements)

References 26 publications

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“…4,5 Among these modes, hand gestures 6 are an important part of human language, and hence, the development of hand gesture recognition affects the nature and flexibility of human-computer interaction. [7][8][9][10][11] In the past few decades, the gesture recognition method is typically based on the angle and position information obtained through data gloves. 12 However, this method is expensive and uses wearable sensors, making the method inconvenient.…”

Section: Introductionmentioning

confidence: 99%

Hand gesture recognition algorithm combining hand-type adaptive algorithm and effective-area ratio for efficient edge computing

Zhang

Xiao

et al. 2021

J. Electron. Imag.

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Most existing gesture recognition algorithms have low recognition rates under rotation, translation, and scaling of hand images as well as different hand types. We propose a new hand gesture recognition algorithm that combines the hand-type adaptive algorithm and effective-area ratio based on feature matching. Samples are divided into several groups according to the subjects' palm shapes and the algorithm is trained using self-collected data. The user's hand type is paired with one of the sample libraries by the hand-type adaptive algorithm. To further improve the accuracy, the effective-area ratio of the gesture is calculated based on the minimum bounding rectangle, and the preliminary gesture is recognized by the effective-area ratio feature method. The results of experiments demonstrate that the proposed algorithm could accurately recognize gestures in real time and exhibits good adaptability to different hand types. The overall recognition rate is over 94%. The recognition rate still exceeds 93% when hand gesture images are rotated, translated, or scaled.

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Section: Introductionmentioning

confidence: 99%

Hand gesture recognition algorithm combining hand-type adaptive algorithm and effective-area ratio for efficient edge computing

Zhang

Xiao

et al. 2021

J. Electron. Imag.

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“…The communication by natural and intuitive noncontact manner is usually considered to be flexible and efficient; many researchers have thus tried efforts to make the machine identify other's intentions and information through the noncontact manner like people, such as sound [1], facial expressions [2], physical movements [3], and gestures [4,5]. Among them, gesture is the most important part of human language, and its development affects the nature and flexibility of human-robot interaction [6][7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Kinect Sensor-Based Long-Distance Hand Gesture Recognition and Fingertip Detection with Depth Information

Peng

2018

Journal of Sensors

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Gesture recognition is an important part of human-robot interaction. In order to achieve fast and stable gesture recognition in real time without distance restrictions, this paper presents an improved threshold segmentation method. The improved method combines the depth information and color information of a target scene with hand position by the spatial hierarchical scanning method; the ROI in the scene is thus extracted by the local neighbor method. In this way, the hand can be identified quickly and accurately in complex scenes and different distances. Furthermore, the convex hull detection algorithm is used to identify the positioning of fingertips in ROI, so that the fingertips can be identified and located accurately. The experimental results show that the hand position can be obtained quickly and accurately in the complex background by using the improved method, the real-time recognition distance interval can be reached by 0.5 m to 2.0 m, and the fingertip detection rates can be reached 98.5% in average. Moreover, the gesture recognition rates are more than 96% by the convex hull detection algorithm. It can be thus concluded that the proposed method achieves good performance of hand detection and positioning at different distances.

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Organising Bodyformation of Modular Autonomous Robots Using Virtual Embryogenesis

Cited by 2 publications

References 26 publications

Hand gesture recognition algorithm combining hand-type adaptive algorithm and effective-area ratio for efficient edge computing

Hand gesture recognition algorithm combining hand-type adaptive algorithm and effective-area ratio for efficient edge computing

Kinect Sensor-Based Long-Distance Hand Gesture Recognition and Fingertip Detection with Depth Information

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