Tracking and Recognising Hand Gestures using Statistical Shape Models.

Ahmad, Tariq; Taylor, Chris; Lanitis, Andreas; Cootes, T. F.

doi:10.5244/c.9.40

Cited by 13 publications

(16 citation statements)

References 9 publications

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“…Research into methods for capturing signing movements directly from video has been reported e.g. [1]. This approach is highly desirable as it obviates the need to record signs by attaching motion sensors to a human, with the attendant problems of invasiveness, motion restriction, calibration, sensor fusion etc.…”

Section: The Signing Avatar Tessamentioning

confidence: 99%

Tessa, a system to aid communication with deaf people

Cox

Lincoln

Tryggvason

et al. 2002

Proceedings of the Fifth International ACM Conference on Assistive Technologies - Assets '02

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TESSA is an experimental system that aims to aid transactions between a deaf person and a clerk in a Post Office by translating the clerk's speech to sign language. A speech recogniser recognises speech from the clerk and the system then synthesizes the appropriate sequence of signs in British Sign language (BSL) using a speciallydeveloped avatar. By using a phrase lookup approach to language translation, which is appropriate for the highly constrained discourse in a Post Office, we were able to build a working system that we could evaluate. We summarise the results of this evaluation (undertaken by deaf users and Post office clerks), and discuss how the findings from the evaluation are being used in the development of an improved system.

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Section: The Signing Avatar Tessamentioning

confidence: 99%

Tessa, a system to aid communication with deaf people

Cox

Lincoln

Tryggvason

et al. 2002

Proceedings of the Fifth International ACM Conference on Assistive Technologies - Assets '02

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show abstract

“…Analysis times are quoted for a SunSparc 20 which operates at 44 m£ops. Other examples of practical applications include analysis of: industrial inspection images (Hunter et al 1994), hand gestures (Ahmad et al 1995), echocardiograms , mammograms (Ellis 1997), surveillance images (Baumberg & Hogg 1994). The method extends to 3D and has been used to interpret 3D MR images of the brain (Hill et al 1993) and knee cartilage (Solloway et al 1996).…”

Section: Pr Ac T Ic a L A Ppl Ic At Ion S Of Ac T I V E S H A Pe Modementioning

confidence: 99%

“…Next, we use this shape information to warp the face image and extract the shape-free patch, which we approximate using the grey-level model to give b grey . Together b shape and b grey provide a complete description from which the image can be reconstructed (Lanitis et al 1995). The dimensionality of the model can be further reduced by modelling the combination of b shape and b grey in a further PCA model which we have termed a`combined appearance model' (Edwards et al 1996).…”

Section: Mode L L I Ng G Loba L G R Ey-l Ev E L a Ppe A R A Nc E : mentioning

confidence: 99%

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Model-based interpretation of complex and variable images

Taylor

Cootes

Lanitis

et al. 1997

Phil. Trans. R. Soc. Lond. B

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The ultimate goal of machine vision is image understandingöthe ability not only to recover image structure but also to know what it represents. By de¢nition, this involves the use of models which describe and label the expected structure of the world. Over the past decade, model-based vision has been applied successfully to images of man-made objects. It has proved much more di¤cult to develop model-based approaches to the interpretation of images of complex and variable structures such as faces or the internal organs of the human body (as visualized in medical images). In such cases it has been problematic even to recover image structure reliably, without a model to organize the often noisy and incomplete image evidence. The key problem is that of variability. To be useful, a model needs to be speci¢cöthat is, to be capable of representing only`legal' examples of the modelled object(s). It has proved di¤cult to achieve this whilst allowing for natural variability. Recent developments have overcome this problem; it has been shown that speci¢c patterns of variability in shape and grey-level appearance can be captured by statistical models that can be used directly in image interpretation. The details of the approach are outlined and practical examples from medical image interpretation and face recognition are used to illustrate how previously intractable problems can now be tackled successfully. It is also interesting to ask whether these results provide any possible insights into natural vision; for example, we show that the apparent changes in shape which result from viewing three-dimensional objects from di¡erent viewpoints can be modelled quite well in two dimensions; this may lend some support to the`characteristic views' model of natural vision.

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“…Processing color-image with a skin-color model and its labeling are used to extract a hand image. Its trajectory is obtained by using the modified BMA (block matching algorithm) from each frame of a sequence of an input image [6] [7] [8]. When this trajectory is analyzed to recognize a gesture according to the predefined window-management rules, the gesture-recognition technique is used to control the display by the window manager [9] [10] [11].…”

Section: Introductionmentioning

confidence: 99%

A Hand Tracking for a Human Computer Interaction System by the Modified Block Matching Algorithm

Kim

2003

Lecture Notes in Computer Science

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Abstract.A GUI (graphical user interface) has been a dominant platform for HCI (human computer interaction). A GUI-based interaction has made computers simpler and easier to use. The GUI-based interaction, however, does not easily support the range of interaction necessary to meet users' needs that are natural, intuitive, and adaptive. In this paper, the modified BMA (block matching algorithm) is proposed to track a hand in a sequence of an image and to recognize it in each video frame in order to replace a mouse with a pointing device for a virtual reality. The HCI system with 30 frames per second is realized in this paper. The modified BMA is proposed to estimate a position of the hand and segmentation with an orientation of motion and a color distribution of the hand region for real-time processing. The experimental result shows that the modified BMA with the YCbCr (luminance Y, component blue, component red) color coordinate guarantees the real-time processing and the recognition rate. The YCbCr color coordinate requires less bits to be coded than the RGB (red, green, blue) color coordinate with omitting the luminance of each pixel color and has less sensitivity to surrounding circumstances. The hand tracking by the modified BMA can be applied to a virtual reality or a game or an HCI system for the disable.

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Tracking and Recognising Hand Gestures using Statistical Shape Models.

Cited by 13 publications

References 9 publications

Tessa, a system to aid communication with deaf people

Tessa, a system to aid communication with deaf people

Model-based interpretation of complex and variable images

A Hand Tracking for a Human Computer Interaction System by the Modified Block Matching Algorithm

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