Name
Abstract | ||
|---|---|---|
We study the influence of motion on the visibility of flicker distortions in naturalistic videos. A series of human subjective studies were executed to understand how motion silences the visibility of flicker distortions as a function of object motion, flicker frequency, and video quality. We found that flicker visibility is strongly reduced when the speed of coherent motion is large, and the effect is pronounced when video quality is poor. Based on this finding, we propose a model of flicker visibility on naturalistic videos. The target-related activation levels in the excitatory layer of neurons were estimated for a displayed video using a spatiotemporal backward masking model, and then the flicker visibility is predicted based on a learned model of neural flicker adaptation processes. Experimental results show that the prediction of flicker visibility using the proposed model correlates well with human perception of flicker distortions. We believe that sufficiently fast and coherent motion silences the perception of flicker distortions on naturalistic videos in agreement with a recently observed \"motion silencing\" effect on synthetic stimuli. We envision that the proposed model could be applied to develop perceptual video quality assessment algorithms that can predict \"silenced\" temporal distortions and account for them when computing quality judgments. We study motion silencing of flicker distortions on naturalistic videos.Flicker visibility is strongly reduced when the speed of object motion is large.Motion silencing of flicker distortions is pronounced when video quality is poor.We propose a model of flicker visibility on naturalistic videos.The model prediction of flicker visibility correlates well with human perception. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1016/j.image.2015.03.006 | Signal Processing: Image Communication |
Keywords | Field | DocType |
Motion silencing,Visual masking,Flicker distortion,Visibility of distortion,Video quality | Flicker,Computer vision,Visibility,Computer science,Perceptual video quality,Artificial intelligence,Perception,Video quality,Visual masking,Model prediction,Backward masking | Journal |
Volume | Issue | ISSN |
39 | PB | 0923-5965 |
Citations | PageRank | References |
8 | 0.50 | 15 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lark Kwon Choi | 1 | 267 | 12.20 |
| Lawrence K. Cormack | 2 | 1044 | 49.38 |
| Alan C. Bovik | 3 | 5062 | 349.55 |