TY - GEN
T1 - Visual analysis of corrupted video data in video event data recorders
AU - Pyo, Youngbin
AU - Lee, Choongin
AU - Lee, Heejo
N1 - Funding Information:
This research was supported by the Public Welfare & Safety Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT and Future planning (2012M3A2A1051118).
Publisher Copyright:
© 2017 IEEE.
PY - 2017/10/18
Y1 - 2017/10/18
N2 - With the rapid proliferation of video event data recorders (VEDRs), video file data from VEDRs are often used as the primary evidence in many fields, such as law enforcement. In this paper, we propose a method for reconstructing corrupted video files and capturing key events recorded in the video file for use as valid evidence. The method first extracts image features from each video frame and constructs a multidimensional vector. Subsequently, dimension reduction of these vectors is performed for visualization in low-dimensional space. The proper sequence of the video frames is restored by using a curve fitting technique for the low-dimensional vectors. Then, we calculate the change in the slope of the curve-fitted model to detect key events in video files. The proposed method generates significant results not provided by existing file recovery techniques.
AB - With the rapid proliferation of video event data recorders (VEDRs), video file data from VEDRs are often used as the primary evidence in many fields, such as law enforcement. In this paper, we propose a method for reconstructing corrupted video files and capturing key events recorded in the video file for use as valid evidence. The method first extracts image features from each video frame and constructs a multidimensional vector. Subsequently, dimension reduction of these vectors is performed for visualization in low-dimensional space. The proper sequence of the video frames is restored by using a curve fitting technique for the low-dimensional vectors. Then, we calculate the change in the slope of the curve-fitted model to detect key events in video files. The proposed method generates significant results not provided by existing file recovery techniques.
KW - Digital forensics
KW - Video event detection
KW - Video sequence reconstruction
KW - Visualization
UR - http://www.scopus.com/inward/record.url?scp=85039897776&partnerID=8YFLogxK
U2 - 10.1109/DESEC.2017.8073828
DO - 10.1109/DESEC.2017.8073828
M3 - Conference contribution
AN - SCOPUS:85039897776
T3 - 2017 IEEE Conference on Dependable and Secure Computing
SP - 453
EP - 458
BT - 2017 IEEE Conference on Dependable and Secure Computing
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2017 IEEE Conference on Dependable and Secure Computing
Y2 - 7 August 2017 through 10 August 2017
ER -