Name
Abstract | ||
|---|---|---|
We introduce a new objective assessment method for visual discomfort of stereoscopic images that makes effective use of the human visual attention model. The proposed method takes into account visual importance regions that play an important role in determining the overall degree of visual discomfort of a stereoscopic image. After obtaining a saliency-based visual importance map for an image, perceptually significant disparity features are extracted to predict the overall degree of visual discomfort. Experimental results show that the proposed method can achieve significantly higher prediction accuracy than the state-of-the-art methods. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/TCSVT.2013.2270394 | IEEE Transactions on Circuits and Systems for Video Technology |
Keywords | Field | DocType |
feature extraction,visual perception | Computer vision,Pattern recognition,Salience (neuroscience),Computer science,Human visual system model,Stereoscopy,Attention model,Feature extraction,Visual Discomfort,Visual attention,Artificial intelligence,Visual perception | Journal |
Volume | Issue | ISSN |
23 | 12 | 1051-8215 |
Citations | PageRank | References |
22 | 0.82 | 15 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yong Ju Jung | 1 | 219 | 18.62 |
| Hosik Sohn | 2 | 265 | 17.25 |
| Seongil Lee | 3 | 231 | 22.07 |
| Hyun Wook Park | 4 | 495 | 54.79 |
| Yong Man Ro | 5 | 1192 | 125.87 |