1. Enhanced-alignment Measure for Binary Foreground Map Evaluation
Deng-Ping Fan1, Cheng Gong1, Yang Cao1, Bo Ren1, Ming-Ming Cheng1, Ali Borji Nankai University Central Florida University
Poster #2351
1. Problem
Image GT Map Noise
IoU, CM[1], 𝑭 𝜷 𝒘 [2], VQ[3], S-measure[4] prefer the noise map.
None of them consider both local and global simultaneously.
[1] Movahedi et al. Design and perceptual validation of performance measures for salient object segmentation. CVPRW, 2010.
[2] Margolin et al. How to evaluate foreground maps? CVPR, 2014.
[3] Shi et al. Visual quality evaluation of image object segmentation: Subjective assessment and objective measure. TIP, 2015.
[4] Fan et al. Structure-measure: A New Way to Evaluate Foreground Maps. ICCV, 2017.
3. Solutions
Bias matrix
Alignment matrix
Enhanced
function
𝜑 𝐼 =𝐼− 𝜇 𝐼 ∙𝐴, 𝜉 𝐹𝑀 = 2 𝜑 𝐺𝑇 ∘ 𝜑 𝐹𝑀 𝜑 𝐺𝑇 ∘ 𝜑 𝐺𝑇 + 𝜑 𝐹𝑀 ∘ 𝜑 𝐹𝑀 , ∅ 𝐹𝑀 =𝑓 𝜉 𝐹𝑀 .
4. Experiments
MM1. Application Ranking
MM4. Human Ranking
GT Rank Rank Rank3
MM2. SOTA vs. Generic
2. Motivation
1. Global information
can be captured by the eye movement.
Image GT Map Generic
MM3. SOTA vs. Noise
2. Local details
recorded by focusing the special image region.
Image GT Map Noise
Examples
5. Results
9.08% to 19.65% improvement vs. popular measures.
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