Vision-based human interface with user-centered frame

Kuno, Yoshinori; Sakamoto, Masanao; Sakata, K.; Shirai, Yoshiaki

doi:10.1109/iros.1994.407586

Cited by 11 publications

(11 citation statements)

References 6 publications

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“…The assumption holds in 3D space under several restrictions; some of them were noted by Lee and Kunii [59], [60]: The palm must be assumed to be rigid, and the fingers can only have a limited number of DoFs. However, most of the models use only 2D locations of fingertips and the palm [3], [28], [57]. Applications that are concerned with deictic gestures usually use only a single (index) fingertip and some other reference point on the hand or body [36], [57], [73].…”

Section: Appearance-based Modelmentioning

confidence: 99%

“…Another common solution to the problem is the use of restrictive backgrounds and clothing (uniform black background and long dark sleeves, for example.) Finally, many of the gesture recognition applications resort to the use of uniquely colored gloves or markers on hands/fingers [19], [28], [57], [60], [62]. The use of background restriction or colored gloves makes it possible to localize the hand efficiently and even in real-time, but imposes the obvious restriction on the user and the interface setup.…”

Section: Localizationmentioning

confidence: 99%

“…However, the detection of fingertip locations in either 3D or 2D space is not trivial. A simple and effective solution to the fingertip detection problem is to use marked gloves or color markers to designate the characteristic fingertips (see [19], [28], [57], [60], [93], for instance). Extraction of fingertip location is then fairly simplified and can be performed using color histogram-based techniques.…”

Section: Features and Detectionmentioning

confidence: 99%

See 2 more Smart Citations

Visual interpretation of hand gestures for human-computer interaction: a review

Pavlović

Sharma

Huang

1997

IEEE Trans. Pattern Anal. Machine Intell.

1,468

646

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Abstract-The use of hand gestures provides an attractive alternative to cumbersome interface devices for human-computer interaction (HCI). In particular, visual interpretation of hand gestures can help in achieving the ease and naturalness desired for HCI. This has motivated a very active research area concerned with computer vision-based analysis and interpretation of hand gestures. We survey the literature on visual interpretation of hand gestures in the context of its role in HCI. This discussion is organized on the basis of the method used for modeling, analyzing, and recognizing gestures. Important differences in the gesture interpretation approaches arise depending on whether a 3D model of the human hand or an image appearance model of the human hand is used. 3D hand models offer a way of more elaborate modeling of hand gestures but lead to computational hurdles that have not been overcome given the real-time requirements of HCI. Appearance-based models lead to computationally efficient "purposive" approaches that work well under constrained situations but seem to lack the generality desirable for HCI. We also discuss implemented gestural systems as well as other potential applications of vision-based gesture recognition. Although the current progress is encouraging, further theoretical as well as computational advances are needed before gestures can be widely used for HCI. We discuss directions of future research in gesture recognition, including its integration with other natural modes of humancomputer interaction.

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Section: Appearance-based Modelmentioning

confidence: 99%

Section: Localizationmentioning

confidence: 99%

Section: Features and Detectionmentioning

confidence: 99%

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Visual interpretation of hand gestures for human-computer interaction: a review

Pavlović

Sharma

Huang

1997

IEEE Trans. Pattern Anal. Machine Intell.

1,468

646

View full text Add to dashboard Cite

show abstract

“…Before recognition, the system should be trained with enough data (refer with: Fig. 4) so that a new feature vector can be classified with good accuracy [9]. The most commonly used hand gesture recognition techniques include: template matching, artificial neural network (ANN), hidden Markov model (HMM) and Geometric features based recognition, etc.…”

Section: Classification and Recognitionmentioning

confidence: 99%

Overview of Hand Gesture Recognition Basic Conceptual Framework

Xu¹,

Dai²

2017

dtetr

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Abstract. With the development of science and technology, human-computer interaction is not only an indispensable technology of research projects such as robot control and IOT, but also has gradually penetrated into the daily life of most people. Because of the inconvenience and dependence on the hard devices of traditional human-computer mode, the finding of more natural human-computer interactive ways is particularly urgent. Hand gesture is vivid, intuitive and contains a lot of interactive information, with same expression ability as natural languages such as spoken language and written language, it can act as a means of natural communication between human and machine. This paper offered an overview of hand gesture recognition including its definition and classification, the general framework of vision based hand gesture recognition was then analyzed in detail.

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“…Ahn [2] have developed augmented interface table using infrared cameras for pervasive environment. Initially researchers have used gloves, color strips or shirt color [3][4][5][6]. Gesture recognition is the phase in which the data analyzed from the visual images of gestures is recognized as a specific gesture.…”

Section: Introductionmentioning

confidence: 99%

GUI system for elders/patients in intensive care

Raheja

Sangwan

Gopinath

et al. 2014

2014 IEEE International Technology Management Conference

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Abstract-In the old age, few people need special care if they are suffering from specific diseases as they can get stroke while they are in normal life routine. Also patients of any age, who are not able to walk, need to be taken care of personally but for this, either they have to be in hospital or someone like nurse should be with them for better care. This is costly in terms of money and man power. A person is needed for 24x7 care of these people. To help in this aspect we purposes a vision based system which will take input from the patient and will provide information to the specified person, who is currently may not in the patient room. This will reduce the need of man power, also a continuous monitoring would not be needed. The system is using MS Kinect for gesture detection for better accuracy and this system can be installed at home or hospital easily. The system provides GUI for simple usage and gives visual and audio feedback to user. This system work on natural hand interaction and need no training before using and also no need to wear any glove or color strip.

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Vision-based human interface with user-centered frame

Cited by 11 publications

References 6 publications

Visual interpretation of hand gestures for human-computer interaction: a review

Visual interpretation of hand gestures for human-computer interaction: a review

Overview of Hand Gesture Recognition Basic Conceptual Framework

GUI system for elders/patients in intensive care

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