The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Saliency-Aware Video Compression
Abstract
In region-of-interest (ROI)-based video coding, ROI parts of the frame are encoded with higher quality than non-ROI parts. At low bit rates, such encoding may produce attention-grabbing coding artifacts, which may draw viewer's attention away from ROI, thereby degrading visual quality. In this paper, we present a saliency-aware video compression method for ROI-based video coding. The proposed method aims at reducing salient coding artifacts in non-ROI parts of the frame in order to keep user's attention on ROI. Further, the method allows saliency to increase in high quality parts of the frame, and allows saliency to reduce in non-ROI parts. Experimental results indicate that the proposed method is able to improve visual quality of encoded video relative to conventional rate distortion optimized video coding, as well as two state-of-the art perceptual video coding methods.
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Cites
Image quality assessment: from error visibility to structural similarity
Wang, Z., Bovik, A. C., Sheikh, H. R., & Simoncelli, E. P. (2004) · IEEE Transactions on Image Processing · doi:10.1109/tip.2003.819861 · Cited by 57,892
A new standardized method for objectively measuring video quality
Pinson, M. H., & Wolf, S. (2004) · IEEE Transactions on Broadcasting · doi:10.1109/tbc.2004.834028 · Cited by 1,182
PEST: Efficient Estimates on Probability Functions
Taylor, M. M., & Creelman, C. D. (1967) · The Journal of the Acoustical Society of America · doi:10.1121/1.1910407 · Cited by 1,173
Video quality assessment using a statistical model of human visual speed perception
Wang, Z., & Li, Q. (2007) · Journal of the Optical Society of America A · doi:10.1364/josaa.24.000b61 · Cited by 210
Cited by
DeepFix: A Fully Convolutional Neural Network for Predicting Human Eye Fixations
Kruthiventi, S. S. S., Ayush, K., & Babu, R. V. (2017) · IEEE Transactions on Image Processing · doi:10.1109/tip.2017.2710620 · Cited by 478
Saliency in VR: How Do People Explore Virtual Environments?
Sitzmann, V., Serrano, A., Pavel, A., Agrawala, M., Gutierrez, D., Masia, B., & Wetzstein, G. (2018) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2018.2793599 · Cited by 459
State-of-the-Art in 360° Video/Image Processing: Perception, Assessment and Compression
Xu, M., Li, C., Zhang, S., & Callet, P. L. (2020) · IEEE Journal of Selected Topics in Signal Processing · doi:10.1109/jstsp.2020.2966864 · Cited by 281
LiveDeep: Online Viewport Prediction for Live Virtual Reality Streaming Using Lifelong Deep Learning
Feng, X., Liu, Y., & Wei, S. (2020) · 2020 IEEE Conference on Virtual Reality and 3D User Interfaces (VR) · doi:10.1109/vr46266.2020.00104 · Cited by 45
Metadata
- Authors
- Hadizadeh, H., & Bajic, I. V.
- Venue
- IEEE Transactions on Image Processing
- Published
- 2014-01
- Volume
- 23
- Issue
- 1
- Pages
- 19-33
- ISSN
- 1057-7149 (ISSN-L)
- 1941-0042
- OpenAlex
- W1978479866
- Cited by
- 326
- References
- 4
- FWCI
- 31.66
- Type
- journal article
- Language
- en
- Open access
- closed
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