A Narrow-Band Video Communication System for the Transmission of Sign Language Over Ordinary Telephone Lines

Abramatic, J.; Letellier, P.; Nadler, Morton

doi:10.1007/978-3-642-81935-3_15

Cited by 9 publications

(6 citation statements)

References 1 publication

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“…On the other hand, we are primarily concerned with intelligibility, and not with appearance, so substantial distortions of the original image may indeed be tolerable. Sperling et al [23] demonstrated a number of binary image transformations that appeared to yield intelligible ASL, as did Pearson and Six [21] and Abramatic, Letellier, and Nadler [22]. Our strategy will be to survey a broad sampling of these transformations in a preliminary study, and to subject the most promising transformations to formal intelligibility tests.…”

Section: Binary Image Transformationsmentioning

confidence: 91%

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Intelligible encoding of ASL image sequences at extremely low information rates

Sperling

Landy

Cohen

et al. 1985

Computer Vision, Graphics, and Image Processing

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American Sign Language (ASL) is a gestural language used by the hearing impaired. This paper describes experimental tests with deaf subjects that compared the most effective known methods of creating extremely compressed ASL images. The minimum requirements for intelligibility were determined for three basically different kinds of transformations: (1) gray-scale transformations that subsample the images in space and time; (2) two-level intensity quantization that converts the gray scale image into a black-and-white approximation; (3) transformations that convert the images into black and white outline drawings (cartoorzr). In Experiment 1, five subjects made quality ratings of 81 kinds of images that varied in spatial resolution, frame rate, and type of transformation. The most promising image size was 96 x 64 pixels (height X width). The 17 most promising image transformations were selected for formal intelligibility testing: 38 deaf subjects viewed 87 ASL sequences l-2 s long of each transformation. The most effective code for gray-scale images is an analog raster code, which can produce images with 0.86 normalized intelligibiliv (Z) at a bandwidth of 2,880 Hz and therefore is transmittable on ordinary 3 KHz telephone circuits. For the binary images, a number of coding schemes are described and compared, the most efficient being an extension of the quadtree method, here termed binquad coding which yielded I = 0.68 at 7,500 bits per second (bps). For cartoons, an even more efficient polygonal transformation, which approximates an outline by COMected straight line segments, is proposed, together with a vectorgraph code yielding, for example, I = 0.56 at 3,900 bps and I = 0.70 at 6,000 bps. Polygonally transformed cartoons offer the possibility of telephonic ASL communication at 4,800 bps. Several combinations of binary image transformations and encoding schemes offer I > 801 at 9,600 bps. 0 1985 Academic Press. Inc.

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Section: Binary Image Transformationsmentioning

confidence: 91%

“…Abramatic, Letellier, Nadler [22] used an edge extraction method based on Gaussian-filtered Laplacian operators (see Sect. 3.3.2) to generate dynamic cartoons of signers on images of 256 X 256 pixels.…”

Section: Early Image-processing Studiesmentioning

confidence: 99%

Intelligible encoding of ASL image sequences at extremely low information rates

Sperling

Landy

Cohen

et al. 1985

Computer Vision, Graphics, and Image Processing

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“…A typical solution is to use different coding techniques. One such technique is model-based coding where image sequences are described by the states (e.g., position, scale, and orientation) of all physical objects in the scene (human participants in the case of VTC) [1], [40]. Only the updates of descriptors are sent while at the receiving end a computer generated model of physical objects is driven using the received data.…”

Section: Applications and Systemsmentioning

confidence: 99%

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

Pavlović

Sharma

Huang

1997

IEEE Trans. Pattern Anal. Machine Intell.

1,456

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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“…Since the early 1980s, image classification and specifically gesture recognition have been a significant part of computer vision research [1]. A large portion of the work has been on improving techniques for image segmentation and motion path recognition as well as object tracking.…”

Section: Introductionmentioning

confidence: 99%

M-VCR: Multi-View Consensus Recognition for Real-Time Experimentation

McKee

Townend

Webster

et al. 2014

2014 IEEE 17th International Symposium on Object/Component/Service-Oriented Real-Time Distributed Computing

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Abstract-A major application area in the computer vision domain is gesture recognition, requiring real-time image classification to respond to human interactions. However, current state-of-the-art high-quality algorithms for image classification do not meet many dynamic real-time requirements. This paper presents the development of M-VCR -a novel approach for improving the reliability of real-time image classification. M-VCR increases the quality of classifications under real-time constraints through the adoption of fast classification algorithms; although these algorithms individually produce lower quality results, utilisation under a 'consensus' approach can achieve results equivalent to those of much higher-quality algorithms. The proposed approach also allows for different algorithms to be utilised in parallel, building on the fault tolerance technique of N-versioning. A significant improvement in image classification is experimentally demonstrated for both the SURF and MSER feature detectors through our integration consensus approach. This improvement is delivered entirely through the integration method without requiring modification of the source algorithms being used.

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A Narrow-Band Video Communication System for the Transmission of Sign Language Over Ordinary Telephone Lines

Cited by 9 publications

References 1 publication

Intelligible encoding of ASL image sequences at extremely low information rates

Intelligible encoding of ASL image sequences at extremely low information rates

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

M-VCR: Multi-View Consensus Recognition for Real-Time Experimentation

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