Video identification based on common features in a scene segmented by CNN

다국어 초록 (Multilingual Abstract)

Video fingerprinting is an important issue in the copyright protection field as digital environment enables the copyright infringement to get easier and easier. Copyright owners want to identify contents on the net and to block infringed contents. In this paper, we propose an efficient algorithm to identify video contents even if we only have a video frame. The algorithm divides a video content into scenes using deep learning network and then extracts common feature from a scene. We use deep learning with convolution neural network for video scene segmentation. It can be more precise than traditional method that use histogram. The feature database contains only a set of common features per a scene. The proposed algorithm can reduce the size of the database by a factor of a hundred, which can reduce the database comparison time by a factor of a few.

목차 (Table of Contents)

• Abstract
• I. Introduction
• II. Related Works
• III. Proposed Methods
• IV. Experiments and Results
• V. Conclusion
• Reference

참고문헌 (Reference)

1 Nah, J., "Video forensic marking algorithm using peak position modulation" 7 (7): 2013

2 Steve Jobs, "Thoughts on Music"

3 Cox, I J., "Secure spread spectrum watermarking for multimedia" 6 (6): 1997

4 Khan, N, Y., "SIFT and SURF performance evaluation against various image deformations on benchmark dataset" 2011

5 Lee, S., "Robust video fingerprinting based on symmetric pairwise boosting" 19 (19): 2009

6 Viola, P., "Rapid object detection using a boosted cascade of simple features" 1 : 2001

7 Wagner, D., "Pose tracking from natural features on mobile phones" IEEE Computer Society 2008

8 Rosten, E., "Machine learning for high-speed corner detection" 2006

9 Dalal, N., "Histograms of oriented gradients for human detection" 1 : 2005

10 Zabih, R., "Feature-based algorithms for detecting and classifying scene breaks" Cornell University 1995

11 Ozuysal, M., "Fast keypoint recognition using random ferns" 32 (32): 2010

12 Lowe, D, G, "Distinctive image features from scale-invariant keypoints" 60 (60): 2004

13 "Digital video fingerprinting"

14 "Digital Rights Management"

15 Mahdi, W., "Automatic video scene segmentation based on spatial-temporal clues and rhythm" 3 (3): 2000

16 Harris, C., "A combined corner and edge detector" 15 (15): 1988