Classifying Covert Photographs

CVPR 2012 POSTER

Outline Introduction Combine Image Features and Attributes Experiment Conclusion

Introduction Why doing this classification?

Image/video acquisition devices New Internet technologies

What is covert? Secret photography

Introduction

Introduction Challenges

Database construction Training set covert:1200 regular:4800 Testing set covert:300 regular:1200

Attribute annotation

Combine Image Features and Attributes

Combine Image Features and Attributes

Low-Level Image Features Bag of Features(BoF) Color GIST Color moments Edge Orientation Histogram Gray Histogram

Combine Image Features and Attributes

Low-Level Image Features Gray Level Co-occurrence Matrix Hue descriptor Local Binary Pattern Pyramid histogram of orientation gradient Spatiogram

Combine Image Features and Attributes

Attribute Classifiers and Attribute Features

Combine Image Features and Attributes

Fusion with Multiple Kernels Learning(MKL)

Combine Image Features and Attributes

Fusion with Multiple Kernels Learning(MKL) Feature normalization and kernel

standardization

Experiment Performance evaluation metrics

AUC 1-EER

Experiment Evaluation of MKL algorithm

Experiment Evaluation of MKL algorithm

Experiment Evaluation of MKL algorithm

Experiment Evaluation of MKL algorithm

Experiment Evaluation of MKL algorithm

Experiment Evaluation of MKL algorithm

Experiment

Conclusion Appropriate features are really important to

the accuracy. Multiple Kernel Learning