閱讀筆記：VISUAL COMFORT ASSESSMENT FOR STEREOSCOPIC 3D IMAGES BASED ON SALIENT DISCOMFORT REGIONS
題目：VISUAL COMFORT ASSESSMENT FOR STEREOSCOPIC 3D IMAGES BASED ON SALIENT DISCOMFORT REGIONS 基於立體3D圖像顯著不舒適區域的視覺舒適度評估 舒適度分數的獲取方法：由顯著權重視差和最大視差加權的視差特徵向量獲得，其中顯著權重視差由色彩顯著圖和視差顯著圖得到 整體框圖： Sc獲取方法:GBVS基於圖像的視覺顯著
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相關文章
- 1. 閱讀筆記：A Visual Comfort Assessment Approach of Stereoscopic Images based on Random Forest Regressor
- 2. 閱讀筆記：Visual comfort assessment for stereoscopic images based on sparse coding with multi-scale dict
- 3. 閱讀筆記:Binocular Fusion Net: Deep Learning Visual Comfort Assessment for Stereoscopic 3D
- 4. 閱讀筆記：VISUALCOMFORTASSESSMENTOFSTEREOSCOPICIMAGES USINGDEEPVISUALANDDISPARITYFEATURESBAS
- 5. 閱讀筆記：Visual comfort evaluated by hue asymmetries in stereoscopic images
- 6. 閱讀筆記：3D visual discomfort predictor based on subjective perceived-constraint sparse representation
- 7. 論文閱讀筆記---MSTGAR: Multioperator-Based Stereoscopic Thumbnail Generation With Arbitrary Resolution
- 8. NIMA：Neural Image Assessment論文閱讀筆記
- 9. 閱讀筆記：3-D Visual Discomfort Assessment Considering Optical and Neural Attention Models
- 10. A Simple Pooling-Based Design for Real-Time Salient Object Detection閱讀筆記