Detection of fingertips in human hand movement sequences

Nölker, Claudia; Ritter, Helge

doi:10.1007/bfb0053001

Cited by 15 publications

(6 citation statements)

References 4 publications

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“…Skeleton [13], dominant points [10], and polar coordinates have been used to detect fingers or fingertips from the extracted hand region; however, these methods encounter difficulty due to noise, scale, and hand direction. Methods that detect hand regions from grayscale images have been proposed [19], [20]; however, only uniform backgrounds were considered. Motion features may be used to track fingers [21], [22], but precise finger motions may not easily be tracked by region motion.…”

Section: Introductionmentioning

confidence: 99%

Vision-Based Finger Action Recognition by Angle Detection and Contour Analysis

Lee¹

2011

ETRI J

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In this paper, we present a novel vision‐based method of recognizing finger actions for use in electronic appliance interfaces. Human skin is first detected by color and consecutive motion information. Then, fingertips are detected by a novel scale‐invariant angle detection based on a variable k‐cosine. Fingertip tracking is implemented by detected region‐based tracking. By analyzing the contour of the tracked fingertip, fingertip parameters, such as position, thickness, and direction, are calculated. Finger actions, such as moving, clicking, and pointing, are recognized by analyzing these fingertip parameters. Experimental results show that the proposed angle detection can correctly detect fingertips, and that the recognized actions can be used for the interface with electronic appliances.

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Section: Introductionmentioning

confidence: 99%

Vision-Based Finger Action Recognition by Angle Detection and Contour Analysis

Lee¹

2011

ETRI J

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“…The use of temperature is not very practical, owing to the expense of infrared cameras [18], dominant points [15], and polar coordinates have been used to detect fingers or fingertips from the extracted hand region; however, these methods encounter difficulty due to noise, scale, and hand direction. Methods that detect hand regions from gray scale images have been proposed [24,25]; only uniform backgrounds were considered. Motion features may be used to track fingers [26,27], but precise finger motions may not easily be tracked by region motion.…”

Section: Proposed Methodologymentioning

confidence: 99%

Finger Detection Algorithm For Computer Mouse Control

Rodrigue¹,

Lee²

2017

Journal of Korea Multimedia Society

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We propose a finger detection algorithm for computer mouse control to control the most commonly actions of a computer mouse(left, right and double click, scroll up and down then we add open and close, minimize and maximize a window, control the mouse.) We use a built-in web camera to control the mouse tasks. We detected, segment, then recognize the hand in our previous papers [1,2]. The user will be able to interact with the computer with the number of fingers detected.

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“…[93] has used Gabor filter to reduce the features from 6400 (80×80) to 35. Some researchers have used different machine learning techniques for significant feature extraction.…”

Section: Significant Features Locationmentioning

confidence: 99%

Hand Gesture Recognition Systems: A Survey

Sarkar¹,

Sanyal²,

Majumder³

2013

IJCA

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Gesture was the first mode of communication for the primitive cave men. Later on human civilization has developed the verbal communication very well. But still nonverbal communication has not lost its weightage. Such nonverbal communication are being used not only for the physically challenged people, but also for different applications in diversified areas, such as aviation, surveying, music direction etc. It is the best method to interact with the computer without using other peripheral devices, such as keyboard, mouse. Researchers around the world are actively engaged in development of robust and efficient gesture recognition system, more specially, hand gesture recognition system for various applications. The major steps associated with the hand gesture recognition system are; data acquisition, gesture modeling, feature extraction and hand gesture recognition. There are several sub-steps and methodologies associated with the above steps. Different researchers have followed different algorithm or sometimes have devised their own algorithm. The current research work reviews the work carried out in last twenty years and a brief comparison has been performed to analyze the difficulties encountered by these systems, as well as the limitation. Finally the desired characteristics of a robust and efficient hand gesture recognition system have been described. General TermsHand gesture recognition, comparison KeywordsData acquisition, gesture modeling, feature extraction, hand gesture recognition INTRODUCTIONGesture is a form of non-verbal communication using various body parts, mostly hand and face. Gesture is the oldest method of communication in human. Primitive men used to communicate the information of food/ prey for hunting, source of water, information about their enemy, request for help etc. within themselves through gestures. Still gestures are used widely for different applications on different domains. This includes human-robot interaction, sign language recognition, interactive games, vision-based augmented reality etc. Another major application of gestures is found in the aviation industry for placing the aircraft in the defined bay after landing, for making the passengers aware about the safety features by the airhostess. For communication by the people at a visible, but not audible distance (surveyors) and by the physically challenged people (mainly the deaf and dumb) gesture is the only method. With the advancement of human civilization, the difficulty of interpersonal communication, not only in terms of language, but also in terms of communication between common people and hearing impaired people is gradually being abolished. If development of sign language is the first step, then development of hand recognition system using computer vision is the second step. Several works have been carried out worldwide using Artificial Intelligence for different sign languages.Human-robot interaction [1] is another area where hand gesture recognition has been successfully used. The use of keyboard and mouse...

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Detection of fingertips in human hand movement sequences

Cited by 15 publications

References 4 publications

Vision-Based Finger Action Recognition by Angle Detection and Contour Analysis

Vision-Based Finger Action Recognition by Angle Detection and Contour Analysis

Finger Detection Algorithm For Computer Mouse Control

Hand Gesture Recognition Systems: A Survey

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