Videoconferencing using spatially varying sensing with multiple and moving foveae

Basu, Anup; Wiebe, Kevin James

doi:10.1109/icpr.1994.577116

Cited by 15 publications

(11 citation statements)

References 7 publications

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“…This has been verified via eye-tracking devices that have been used to track the viewer's eye movements [8]. Attention-based coding schemes have then been designed to take advantage of the viewer's varying spatial resolution within each frame [8][9][10]. This approach requires two different, but related issues to be solved: attentive processing and spatio-temporal pre-processing for coding.…”

Section: Related Literaturementioning

confidence: 99%

“…Many different approaches have been proposed for finding the foveal regions. In adaptive foveated coding, it is assumed that a fovea corresponds to a small region around the center of an incoming frame [9]. A new frame that has a higher resolution at the center is created via applying variable resolution transform around this center point.…”

Section: Related Literaturementioning

confidence: 99%

“…Some approaches pre-process the image spatially while the redundancy along the temporal dimension is not utilized at all [9]. A foveated coding scheme has been proposed in [12].…”

Section: Related Literaturementioning

confidence: 99%

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Attention-based video streaming

Dikici

Bozma

2010

Signal Processing: Image Communication

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Section: Related Literaturementioning

confidence: 99%

Section: Related Literaturementioning

confidence: 99%

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Attention-based video streaming

Dikici

Bozma

2010

Signal Processing: Image Communication

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“…Since a foveated image carries much less information compared to the original uniform image, it can be encoded by fewer number of bytes. This observation has been exploited by visualization systems where transmission of images to the display device is a bottleneck, for example, in video conferencing [2,3,11]. Foveation also plays a role in visualization systems where the image rendering process is not fast enough to meet the real-time requirement, for example in volume visualization [16] and flight simulation [12,31].…”

Section: Applications Of Foveationmentioning

confidence: 99%

Wavelet Foveation

Chang

Mallat

Yap

2000

Applied and Computational Harmonic Analysis

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A foveated image is a nonuniform resolution image whose resolution is highest at a point (fovea) but falls off away from the fovea. It can be obtained from a uniform image through a space-variant smoothing process, where the width of the smoothing function is small near the fovea and gradually expanding as the distance from the fovea increases. We treat this process as an integral operator and analyze its kernel. This kernel is dominated by its diagonal in the wavelet bases and thus permits a fast algorithm for foveating images. In addition, the transformed kernel takes a simple form which can be easily computed using a look-up table. This is useful, since in applications the fovea changes rapidly. We describe an application of our approximation algorithm in image visualization over the Internet.

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“…This distribution of resolution provides a fast and simple way of reducing information in the visual field without sacrificing the size of the visual field and the resolution around the fovea. As the biological visual system is highly effective, its space-variant nature has inspired the design of many computer vision systems that resemble the biological foveated vision [1,4,21], video conferencing [2,8], image compression [5], and visualization systems [13]. The foveated image is obtained from the uniform resolution image through a space-variant smoothing process where the width of the smoothing function is small near the fovea but gradually increases toward the periphery.…”

Section: Wavelet Foveationmentioning

confidence: 99%

Robust image authentication using content based compression

et al. 2003

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Abstract. Image authentication is becoming very important for certifying data integrity. A key issue in image authentication is the design of a compact signature that contains sufficient information to detect illegal tampering yet is robust under allowable manipulations. In this paper, we recognize that most permissible operations on images are global distortions like low-pass filtering and JPEG compression, whereas illegal data manipulations tend to be localized distortions. To exploit this observation, we propose an image authentication scheme where the signature is the result of an extremely low-bit-rate content-based compression. The content-based compression is guided by a space-variant weighting function whose values are higher in the more important and sensitive region. This spatially dependent weighting function determines a weighted norm that is particularly sensitive to the localized distortions induced by illegal tampering. It also gives a better compactness compared to the usual compression schemes that treat every spatial region as being equally important. In our implementation, the weighting function is a multifovea weighted function that resembles the biological foveated vision system. The foveae are salient points determined in the scale-space representation of the image. The desirable properties of multifovea weighted function in the wavelet domains fit nicely into our scheme. We have implemented our technique and tested its robustness and sensitivity for several manipulations.

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Videoconferencing using spatially varying sensing with multiple and moving foveae

Cited by 15 publications

References 7 publications

Attention-based video streaming

Attention-based video streaming

Wavelet Foveation

Robust image authentication using content based compression

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