1. Date of download: 6/9/2016 Copyright © 2016 SPIE. All rights reserved. Basic stages involved in the design of a classification system. Figure Legend: From: Spatial dependence matrix feature and redundancy elimination algorithm using AdaBoost for object detection Opt. Eng. 2011;50(5):057202-057202-16. doi:10.1117/1.3572123

2. Date of download: 6/9/2016 Copyright © 2016 SPIE. All rights reserved. Representation comparison of car structural characteristics between spatial dependence matrix feature and conventional Haar-like three-rectangle features. Figure Legend: From: Spatial dependence matrix feature and redundancy elimination algorithm using AdaBoost for object detection Opt. Eng. 2011;50(5):057202-057202-16. doi:10.1117/1.3572123

3. Date of download: 6/9/2016 Copyright © 2016 SPIE. All rights reserved. Conventional Haar-like feature structures and some of variants: a) commonly used conventional HL features; b) variant of proportional expansion of a rectangle feature; c) variant for nonadjacent rectangle feature. Figure Legend: From: Spatial dependence matrix feature and redundancy elimination algorithm using AdaBoost for object detection Opt. Eng. 2011;50(5):057202-057202-16. doi:10.1117/1.3572123

4. Date of download: 6/9/2016 Copyright © 2016 SPIE. All rights reserved. Spatial dependence matrix feature window and subwindow. Figure Legend: From: Spatial dependence matrix feature and redundancy elimination algorithm using AdaBoost for object detection Opt. Eng. 2011;50(5):057202-057202-16. doi:10.1117/1.3572123

5. Date of download: 6/9/2016 Copyright © 2016 SPIE. All rights reserved. AdaBoost feature selection algorithm in Ref.. Figure Legend: From: Spatial dependence matrix feature and redundancy elimination algorithm using AdaBoost for object detection Opt. Eng. 2011;50(5):057202-057202-16. doi:10.1117/1.3572123

6. Date of download: 6/9/2016 Copyright © 2016 SPIE. All rights reserved. AdaBoostWREA feature selection algorithm. Figure Legend: From: Spatial dependence matrix feature and redundancy elimination algorithm using AdaBoost for object detection Opt. Eng. 2011;50(5):057202-057202-16. doi:10.1117/1.3572123

7. Date of download: 6/9/2016 Copyright © 2016 SPIE. All rights reserved. Elimination redundancy algorithm. Figure Legend: From: Spatial dependence matrix feature and redundancy elimination algorithm using AdaBoost for object detection Opt. Eng. 2011;50(5):057202-057202-16. doi:10.1117/1.3572123

8. Date of download: 6/9/2016 Copyright © 2016 SPIE. All rights reserved. Boolean elimination redundancy algorithm. Figure Legend: From: Spatial dependence matrix feature and redundancy elimination algorithm using AdaBoost for object detection Opt. Eng. 2011;50(5):057202-057202-16. doi:10.1117/1.3572123

9. Date of download: 6/9/2016 Copyright © 2016 SPIE. All rights reserved. Error rate. Figure Legend: From: Spatial dependence matrix feature and redundancy elimination algorithm using AdaBoost for object detection Opt. Eng. 2011;50(5):057202-057202-16. doi:10.1117/1.3572123

10. Date of download: 6/9/2016 Copyright © 2016 SPIE. All rights reserved. Number of different features selected by the resultant classifiers. Figure Legend: From: Spatial dependence matrix feature and redundancy elimination algorithm using AdaBoost for object detection Opt. Eng. 2011;50(5):057202-057202-16. doi:10.1117/1.3572123

11. Date of download: 6/9/2016 Copyright © 2016 SPIE. All rights reserved. Illustration of selected features by the resultant classifiers. Figure Legend: From: Spatial dependence matrix feature and redundancy elimination algorithm using AdaBoost for object detection Opt. Eng. 2011;50(5):057202-057202-16. doi:10.1117/1.3572123

12. Date of download: 6/9/2016 Copyright © 2016 SPIE. All rights reserved. Influence of parameter λ with a fixed γ = 1.0. (a) Shows the elimination feature number for different λ and (b) shows the error rates with respect to λ. Figure Legend: From: Spatial dependence matrix feature and redundancy elimination algorithm using AdaBoost for object detection Opt. Eng. 2011;50(5):057202-057202-16. doi:10.1117/1.3572123

13. Date of download: 6/9/2016 Copyright © 2016 SPIE. All rights reserved. Influence of parameter γwith a fixed λ(0.5). (a) Shows the elimination feature number for different γ and (b) shows the error rates with respect to γ. Figure Legend: From: Spatial dependence matrix feature and redundancy elimination algorithm using AdaBoost for object detection Opt. Eng. 2011;50(5):057202-057202-16. doi:10.1117/1.3572123

14. Date of download: 6/9/2016 Copyright © 2016 SPIE. All rights reserved. Impact of elimination redundancy features on training speed. (a) Shows the elimination feature number curve for three specificλandγ and (b) shows the time-consumed versus stages number. Figure Legend: From: Spatial dependence matrix feature and redundancy elimination algorithm using AdaBoost for object detection Opt. Eng. 2011;50(5):057202-057202-16. doi:10.1117/1.3572123

15. Date of download: 6/9/2016 Copyright © 2016 SPIE. All rights reserved. Comparison of our algorithm with conventional AdaBoost (Ref. ). (a) Shows testing error rates of the four algorithms and (b) shows the ROC curves for the four algorithms. Figure Legend: From: Spatial dependence matrix feature and redundancy elimination algorithm using AdaBoost for object detection Opt. Eng. 2011;50(5):057202-057202-16. doi:10.1117/1.3572123