Image Categorization Dog or Cat

1. Image CategorizationDog or Cat Grace Akpan Hehe Feng Junci Wang MehranJavanmardi YuanyuanGao

2. Kaggle http://www.kaggle.com/c/dogs-vs-cats • Microsoft Asirra CAPTCHA • Caltech (object recognition) Introduction

3. Detecting whether image contains a dog or cat Purpose

4. Why we are interested in this problem? • Classification Method used in the previous articles • Challenge: Feature Extraction • Feature Extraction Methods we determine to use: • Scale Invariant Feature Transform (SIFT) • K – means Clustering • Bag of Visual Words • Image Tiling Problem Definition

5. Dense key points • Sift descriptors • K – means Clustering • Bag of words: Histogram • Tiling (creating sub-images) • Spatial histograms for each sub-image Procedure

6. 10 Dense Key Points 10

7. Sift Descriptors • Noise Robust • Scale Invariant • Rotation Invariant • Viewpoint Invariant • Illumination Invariant

8. K – means Clustering Bag of words

9. Tiling

10. Spatial histograms Bag of words: 4000*4 + 4000 = 20000 # of clusters *4 + # of clusters

11. Whole Procedure

12. Given: • 1 : training 4000 images containing cat • 0: training 4000 images containing dog • Classify: Train/Apply the Model ？

13. Accuracy (1000 images of dog and 1000 images of cat) Results/Conclusion

14. The size of the pictures • The orientation of the pictures • Irrelevant pictures • Hyper-parameters • Memory problem • Long processing time Discussions

15. Test with some refined data (only face of cat/dog): • Add face detection Improvement/ Future Work Training set: 660 Testing set: 110 Clusters: 50 Accuracy :76.4% Verifying accuracy (test on training set): 99.54%

16. Open source library provided by VLFeat.org http://www.vlfeat.org/ • Suggest strategy provided by Prof. Andrea Vedaldi and Andrew Zisserman research group from University of Oxford http://www.robots.ox.ac.uk/~vgg/share/practical-image- classification.htm • Parkhi, Omkar M., et al. "The truth about cats and dogs." Computer Vision (ICCV), 2011 IEEE International Conference on. IEEE, 2011. • Belokurov, V., et al. "Cats and dogs, hair and a hero: a quintet of new Milky Way companions." The Astrophysical Journal 654.2 (2007): 897. • Golle, Philippe. "Machine learning attacks against the AsirraCAPTCHA."Proceedings of the 15th ACM conference on Computer and communications security. ACM, 2008. External Sources/ References

17. Dr. Jurvan den Berg • Dustin Webb / Brig Bagley / Liang He • Each Team member Yuanyuan Acknowledgement Hehe Mehran Junci Grace

18. Questions?

20. SIFT details