The significance of eye movements and image acceleration for coding television image sequences
Digital images and human vision
The visible differences predictor: an algorithm for the assessment of image fidelity
Digital images and human vision
Algorithms for Defining Visual Regions-of-Interest: Comparison with Eye Fixations
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Formal Model for Video Shot Segmentation and its Application via Animate Vision
Multimedia Tools and Applications
Digital Video Image Quality and Perceptual Coding (Signal Processing and Communications)
Digital Video Image Quality and Perceptual Coding (Signal Processing and Communications)
Foveated video quality assessment
IEEE Transactions on Multimedia
Embedded foveation image coding
IEEE Transactions on Image Processing
Automatic foveation for video compression using a neurobiological model of visual attention
IEEE Transactions on Image Processing
GAFFE: A Gaze-Attentive Fixation Finding Engine
IEEE Transactions on Image Processing
Fast algorithms for foveated video processing
IEEE Transactions on Circuits and Systems for Video Technology
Foveated shot detection for video segmentation
IEEE Transactions on Circuits and Systems for Video Technology
A practical foveation-based rate-shaping mechanism for MPEG videos
IEEE Transactions on Circuits and Systems for Video Technology
A scalable wavelet-based video distortion metric and applications
IEEE Transactions on Circuits and Systems for Video Technology
Bayesian Integration of Face and Low-Level Cues for Foveated Video Coding
IEEE Transactions on Circuits and Systems for Video Technology
Modeling motion visual perception for video quality assessment
MM '11 Proceedings of the 19th ACM international conference on Multimedia
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Efficiency of a video coding process, as well as accuracy of an objective video quality evaluation can be significantly improved by introduction of the human visual system (HVS) characteristics. In this paper we analyze one of these characteristics; namely, visual acuity reduction due to the foveated vision and object movements in a video sequence. We propose a new video quality metric called Foveated Mean Squared Error (FMSE) that takes into account a variable resolution of the HVS across the visual field. The highest visual acuity is at the point of fixation that falls into fovea, an area at retina with the highest density of photoreceptors. Visual acuity decreases rapidly for image regions which are further with respect to the fixation point. FMSE also utilizes the effect of additional spatial acuity reduction due to motion in a video sequence. The quality measures calculated by FMSE have shown a high correlation with experimental results obtained by subjective video quality assessment.