Real-time foveation techniques for H.263 video encoding in software

Sheikh, H.R.; Liu, Shizhong; Evans, Brian L.; Bovik, A.C.

doi:10.1109/icassp.2001.941286

Cited by 16 publications

(25 citation statements)

References 4 publications

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“…Results reported of substantial bitrate reduction due to foveation with minimal perceptual loss in image quality. Foveated compression, mainly adapted for real-time usage, has been extended to video Perry 1998, 1999], and has been investigated in several other papers [Sheikh et al 2001;Wang and Bovik 2001;Bergström 2003;Wang et al 2003]. …”

Section: Introductionmentioning

confidence: 99%

Effect of compressed offline foveated video on viewing behavior and subjective quality

Nyström

Holmqvist

2010

ACM Trans. Multimedia Comput. Commun. Appl.

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Offline foveation is a technique to improve the compression efficiency of digitized video. The general idea behind offline foveation is to blur video regions where no or a small number of previewers look without decreasing the subjective quality for later viewers. It relies on the fact that peripheral vision is reduced compared to central vision, and the observation that during free-viewing humans' gaze positions generally coincide when watching video. In this article, we conduct two experiments to assess how offline foveation affects viewing behavior and subjective quality. In the first experiment, 15 subjects free-viewed six video clips before and after offline foveation whereas in the second experiment we had 17 subjects assessing the quality of these videos after one, two, and three consecutive viewings. Eye movements were measured during the experiments. Results showed that, although offline foveation prior to encoding with H.264 yielded data reductions up to 52% (20% average) on the tested videos, it had little or no effect on where people looked, their intersubject dispersion, fixation duration, saccade amplitude, or the experienced quality during first-time viewing. However, seeing the videos more than once increased the intersubject dispersion and decreased the subjective quality. In view of these results, we discuss the usage of offline foveated video in practical applications.

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Section: Introductionmentioning

confidence: 99%

Effect of compressed offline foveated video on viewing behavior and subjective quality

Nyström

Holmqvist

2010

ACM Trans. Multimedia Comput. Commun. Appl.

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“…Here we present multiplierless triangular-transition weights given in (15). We observed from experiments that the performance in terms of blocking artifacts, subjective quality and output rate of these weights are as good as the weights designed from the filters in [22]:…”

Section: B3 Designing Dct Subband Weightsmentioning

confidence: 98%

“…We would therefore like to use weights that have smoother transitions from unity to zero. Design of smoother DCT weights from lowpass filters has been explored in [22]. However we would like to keep the benefits of the weights designed in [22] but still reduce complexity by eliminating the need to perform multiplications.…”

Section: B3 Designing Dct Subband Weightsmentioning

confidence: 99%

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Real-time foveation techniques for low bit rate video coding

2003

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Lossy video compression methods often rely on modeling the abilities and limitations of the intended receiver, the Human Visual System (HVS), to achieve the highest possible compression with as little effect on perceived quality as possible. Foveation, which is nonuniform resolution perception of the visual stimulus by the HVS due to the non-uniform density of photoreceptor cells in the eye, has been demonstrated to be useful for reducing bit rates beyond the abilities of uniform resolution video coders. In this work, we present realtime foveation techniques for low bit rate video coding. First, we develop an approximate model for foveation. Then, we demonstrate that foveation, as described by this model, can be incorporated into standard motion compensation and Discrete Cosine Transform (DCT) based video coding techniques for low bit rate video coding, such as the H.263 or MPEG-4 video coding standards, without incurring prohibitive complexity overhead. We demonstrate that foveation in the DCT domain can actually result in computational speedups. The techniques presented can be implemented using the baseline modes in the video coding standards and do not require any modification to, or post processing at, the decoder.

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“…By taking advantage of the this effect, considerable high frequency information redundancy can be removed from the peripheral regions without significant loss of the reconstructed image and video quality. The foveation factor has been employed in previous work to improve image and video coding efficiency [24]- [36]. Foveated image and video coding is closely related to Region-ofInterest (ROI) image and video coding (e.g., [37]- [40]).…”

Section: Introductionmentioning

confidence: 99%

Foveation scalable video coding with automatic fixation selection

Wang

Bovik

2003

IEEE Trans. on Image Process.

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163

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Abstract-Image and video coding is an optimization problem. A successful image and video coding algorithm delivers a good tradeoff between visual quality and other coding performance measures, such as compression, complexity, scalability, robustness, and security. In this paper, we follow two recent trends in image and video coding research. One is to incorporate human visual system (HVS) models to improve the current state-of-the-art of image and video coding algorithms by better exploiting the properties of the intended receiver. The other is to design rate scalable image and video codecs, which allow the extraction of coded visual information at continuously varying bit rates from a single compressed bitstream.Specifically, we propose a foveation scalable video coding (FSVC) algorithm which supplies good quality-compression performance as well as effective rate scalability. The key idea is to organize the encoded bitstream to provide the best decoded video at an arbitrary bit rate in terms of foveated visual quality measurement. A foveation-based HVS model plays an important role in the algorithm. The algorithm is adaptable to different applications, such as knowledge-based video coding and video communications over time-varying, multi-user and interactive networks.

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Real-time foveation techniques for H.263 video encoding in software

Cited by 16 publications

References 4 publications

Effect of compressed offline foveated video on viewing behavior and subjective quality

Effect of compressed offline foveated video on viewing behavior and subjective quality

Real-time foveation techniques for low bit rate video coding

Foveation scalable video coding with automatic fixation selection

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