Vision-Based Hand Gesture Recognition for Understanding Musical Time Pattern and Tempo

Je, Hong-Mo; Kim, Jiman; Kim, Daijin

doi:10.1109/iecon.2007.4460080

Cited by 4 publications

(2 citation statements)

References 6 publications

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“…In musical performances, some use the Kinect to recognize drum-hitting gestures [9]. In musical conducting, hand gestures are used to express the conductor's style and emotion and to make performers understand the conductor's guidance [10,11]. Although every conductor has their own style of conducting, a standard conducting rule exists.…”

Section: Introductionmentioning

confidence: 99%

Real-Time Musical Conducting Gesture Recognition Based on a Dynamic Time Warping Classifier Using a Single-Depth Camera

Chin-Shyurng

Lee

2019

Applied Sciences

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Gesture recognition is a human−computer interaction method, which is widely used for educational, medical, and entertainment purposes. Humans also use gestures to communicate with each other, and musical conducting uses gestures in this way. In musical conducting, conductors wave their hands to control the speed and strength of the music played. However, beginners may have a limited comprehension of the gestures and might not be able to properly follow the ensembles. Therefore, this paper proposes a real-time musical conducting gesture recognition system to help music players improve their performance. We used a single-depth camera to capture image inputs and establish a real-time dynamic gesture recognition system. The Kinect software development kit created a skeleton model by capturing the palm position. Different palm gestures were collected to develop training templates for musical conducting. The dynamic time warping algorithm was applied to recognize the different conducting gestures at various conducting speeds, thereby achieving real-time dynamic musical conducting gesture recognition. In the experiment, we used 5600 examples of three basic types of musical conducting gestures, including seven capturing angles and five performing speeds for evaluation. The experimental result showed that the average accuracy was 89.17% in 30 frames per second.

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Section: Introductionmentioning

confidence: 99%

Real-Time Musical Conducting Gesture Recognition Based on a Dynamic Time Warping Classifier Using a Single-Depth Camera

Chin-Shyurng

Lee

2019

Applied Sciences

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“…As 3D hand models are quite complex, the classification of gestures from 3D models is computationally intensive making real-time implementation difficult. On the other hand, the 2D approach is restricted to the less complex problem of classifying well-defined static gestures [5][6][7][8].…”

Section: T I Introductionmentioning

confidence: 99%

Human computer interaction using hand gesture

Wan

Nguyen

2008

2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society

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Hand gesture is a very natural form of human interaction and can be used effectively in human computer interaction (HCI). This project involves the design and implementation of a HCI using a small hand-worn wireless module with a 3-axis accelerometer as the motion sensor. The small stand-alone unit contains an accelerometer and a wireless Zigbee transceiver with microcontroller. To minimize intrusiveness to the user, the module is designed to be small (3cm by 4 cm). A time-delay neural network algorithm is developed to analyze the time series data from the 3-axis accelerometer. Power consumption is reduced by the non-continuous transmission of data and the use of low-power components, efficient algorithm and sleep mode between sampling for the wireless module. A home control interface is designed so that the user can control home appliances by moving through menus. The results demonstrate the feasibility of controlling home appliances using hand gestures and would present an opportunity for a section of the aging population and disabled people to lead a more independent life.

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Head-Computer Interface: A Multimodal Approach to Navigate through Real and Virtual Worlds

Carrino

Tscherrig

Mugellini

et al. 2011

Lecture Notes in Computer Science

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Vision-Based Hand Gesture Recognition for Understanding Musical Time Pattern and Tempo

Cited by 4 publications

References 6 publications

Real-Time Musical Conducting Gesture Recognition Based on a Dynamic Time Warping Classifier Using a Single-Depth Camera

Real-Time Musical Conducting Gesture Recognition Based on a Dynamic Time Warping Classifier Using a Single-Depth Camera

Human computer interaction using hand gesture

Head-Computer Interface: A Multimodal Approach to Navigate through Real and Virtual Worlds

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