New hand gesture recognition method for mouse operations

Haq, Ehsan Ul; Pirzada, Syed Jahanzeb Hussain; Baig, Mirza Waqar; Shin, Hyunchul

doi:10.1109/mwscas.2011.6026330

Cited by 11 publications

(3 citation statements)

References 14 publications

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“…Towards the success of any ICT initiative intended for under privileged illiterate masses, it is extremely critical to have a user friendly mechanism to use the system, without which no ICT program can be successful on the ground. There are many gesture based techniques (Ul Haq et al, 2011;Juan et al, 2011;Nitish and Unnikrishnan, 2012), but these are not suitable for people with lower level of cognitive abilities. The design of input devices considering the cognitive abilities of intended users and prevailing rural eco system is major challenge.…”

Section: Introductionmentioning

confidence: 99%

Efficacy of Numeric Keypad for Computer Illiterates in Rural ICT

Dutta¹,

Kumar²,

Sridharan³

et al. 2015

Journal of Computer Science

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The world has a vast population of illiterate people who cannot read and write. There are globally about 781 million adults today who fall into this category of illiterate population. The number is even higher for computer illiterates, as not all literate masses qualify to be computer literate due to various compelling factors prevailing. There has been a lot of focus in recent times by both governmental and nongovernmental agencies to extend the proliferation of ICT among computer illiterates, especially in the rural areas. This focus is prevalent both worldwide and as well as in India. India has around 37% of world's illiterate population. One of the major bottleneck and hindrance towards achieving penetration objective is due to the lack of a suitable Human Computer Interface (HCI) system addressing the specific needs of the computer illiterate section. In this study, we discuss the various aspects of input devices for this segment. We analyze the efficacy of a simplified numeric keypad as a HCI in an information dissemination system for computer illiterates specifically in the context of rural area usage.

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Section: Introductionmentioning

confidence: 99%

Efficacy of Numeric Keypad for Computer Illiterates in Rural ICT

Dutta¹,

Kumar²,

Sridharan³

et al. 2015

Journal of Computer Science

View full text Add to dashboard Cite

show abstract

“…The problem of hand gesture recognition has been given a considerable research attention due to a wide range of its practical applications, including humancomputer interfaces [1,2], virtual reality [3], telemedicine [4], videoconferencing [5], and more [6,7]. The proposed approaches can be divided into hardwareand vision-based methods.…”

Section: Introductionmentioning

confidence: 99%

Fast and Accurate Hand Shape Classification

Nalepa

Kawulok

2014

Communications in Computer and Information Science

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Abstract. The problem of hand shape classification is challenging since a hand is characterized by a large number of degrees of freedom. Numerous shape descriptors have been proposed and applied over the years to estimate and classify hand poses in reasonable time. In this paper we discuss our parallel framework for real-time hand shape classification applicable in real-time applications. We show how the number of gallery images influences the classification accuracy and execution time of the parallel algorithm. We present the speedup and efficiency analyses that prove the efficacy of the parallel implementation. Noteworthy, different methods can be used at each step of our parallel framework. Here, we combine the shape contexts with the appearance-based techniques to enhance the robustness of the algorithm and to increase the classification score. An extensive experimental study proves the superiority of the proposed approach over existing state-of-the-art methods.

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“…Hand gestures constitute an important source of non-verbal communication, either complementary to the speech, or the primary one for people with disabilities. The problem of hand gesture recognition has been given a considerable research attention due to a wide range of its practical applications, including humancomputer interfaces [1,2], virtual reality [3], telemedicine [4], videoconferencing [5], and more [6,7]. The proposed approaches can be divided into hardwareand vision-based methods.…”

Section: Introductionmentioning

confidence: 99%

Real-Time Hand Shape Classification

Nalepa,

Kawulok

2014

Preprint

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The problem of hand shape classification is challenging since a hand is characterized by a large number of degrees of freedom. Numerous shape descriptors have been proposed and applied over the years to estimate and classify hand poses in reasonable time. In this paper we discuss our parallel framework for real-time hand shape classification applicable in real-time applications. We show how the number of gallery images influences the classification accuracy and execution time of the parallel algorithm. We present the speedup and efficiency analyses that prove the efficacy of the parallel implementation. Noteworthy, different methods can be used at each step of our parallel framework. Here, we combine the shape contexts with the appearance-based techniques to enhance the robustness of the algorithm and to increase the classification score. An extensive experimental study proves the superiority of the proposed approach over existing state-of-the-art methods.

show abstract

New hand gesture recognition method for mouse operations

Cited by 11 publications

References 14 publications

Efficacy of Numeric Keypad for Computer Illiterates in Rural ICT

Efficacy of Numeric Keypad for Computer Illiterates in Rural ICT

Fast and Accurate Hand Shape Classification

Real-Time Hand Shape Classification

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