Single- and Cross- Database Benchmarks for Gender Classification Under Unconstrained Settings

Transcripción

1 Single- and Cross- Database Benchmarks for Gender Classification Under Unconstrained Settings November 3, 20

2 Outline. Motivation 2. Databases 3. Proposed system 4. Test protocol 5. Results 6. Conclusions November 3, 20

3 Motivation Increasing application areas for gender recognition Realistic performance estimation No standardized evaluation protocols Check suitability of different real-world databases November 3, 20

4 Databases FERET Database Controlled conditions Limited demography Small number of images November 3, 20

5 Databases LFW Database Large database Commonly used for face recognition Benchmark for gender classification proposed for this challenge November 3, 20

6 Databases Gallagher s Database Demographic variability Different environments and conditions Very large database November 3, 20

7 Proposed system ROI size: 90x05 Features Energy % Classifier 05x20 Pixels Linear SVM Gabor jets LDA LBPs November 3, 20

8 Evaluation protocol 5- fold division (following BeFIT Gender Classification challenge) LFW: 029 male and 2959 female faces Gallagher s: 7380 male and 7380 female faces Single-Database protocol November 3, 20

9 Evaluation protocol Cross-Database protocol November 3, 20

10 Evaluation protocol Metrics: Tests: Gallagher s Gallagher s LFW LFW Gallagher s LFW LFW Gallagher s Single-Database Cross-Database November 3, 20

11 Results PCA+SVM PCA+LDA Gallagher s Gallagher s Pixels Gabor jets LBPs 90x05 05x20 90x05 05x20 90x05 05x20 ACC TPR TNR ACC TPR TNR Similar behaviour of SVM and LDA Best configuration: 05x20 ROI, Gabor jets Balanced TPR and TNR November 3, 20

12 Results LFW LFW Higher ACC rates Great TPR-TNR imbalance November 3, 20

13 Results LFW LFW Similar ACC rate More balanced TPR and TNR More parameters to determine November 3, 20

14 Results Gallagher s LFW Higher ACC than intra-gallagher TPR-TNR imbalance (9% difference) November 3, 20

15 Results LFW Gallagher s Lower ACC than intra-lfw tests TPR-TNR imbalance November 3, 20

16 Results LFW Gallagher s Lower ACC than intra-lfw tests Similar ACC to non-weighted SVM TPR-TNR imbalance (inverted) November 3, 20

17 Conclusions Standardized protocol for Gallagher s (public) Single- Database experiments: 05x20 ROI performs better Gabor jets and LBPs better than pixels Linear SVM and LDA have similar performance Balanced TPR and TNR in Gallagher s, not in LFW Pixels Gabor LBPs Ours 79.6% 86.6% 86.34% Others [] 69.96% [2] 75.7% [2] 77.4% [] A. Gallagher and T. Chen. Understanding Images of groups of People, CVPR09. [2] C. Shan. Learning local features for age estimation on real-life faces, MPVA0. November 3, 20

18 Conclusions Cross- Database experiments Good generalization properties with Gallagher s Good performance estimate with Gallagher s LFW causes TPR-TNR imbalance November 3, 20

19 Thank you for your attention! Pablo Dago-Casas Daniel González-Jiménez Long Long Yu José Luis Alba-Castro Contact info: November 3, 20