TY - GEN
T1 - Lightweight searchable screen video recording
AU - Marder, Mattias
AU - Geva, Amir
AU - Ruan, Yaoping
PY - 2012/12/1
Y1 - 2012/12/1
N2 - Command logging of maintenance and operation activities of modern computer systems has become an integral component of customer and audit requirements. In recent years, this logging has usually been achieved via desktop video recording. However, the conventional approach of video recording requires high computation overhead, high network bandwidth, and a large storage size. Searching through video files is also a challenge. In this paper, we present a lossy, but text text-preserving, compression scheme that meets these challenges by creating a sparse bitonal image suitable for optical character recognition (OCR). Using our system for auditing, the bitonal image gets stored on a server. Due to the mechanism's text-preserving compression, we can apply OCR off-line to create annotations of each video frame, making the output searchable. Compared to state-of-the-art compression of raw video, our approach can reduce file size by 50-80%, while using CPU and memory resources similar to other methods.
AB - Command logging of maintenance and operation activities of modern computer systems has become an integral component of customer and audit requirements. In recent years, this logging has usually been achieved via desktop video recording. However, the conventional approach of video recording requires high computation overhead, high network bandwidth, and a large storage size. Searching through video files is also a challenge. In this paper, we present a lossy, but text text-preserving, compression scheme that meets these challenges by creating a sparse bitonal image suitable for optical character recognition (OCR). Using our system for auditing, the bitonal image gets stored on a server. Due to the mechanism's text-preserving compression, we can apply OCR off-line to create annotations of each video frame, making the output searchable. Compared to state-of-the-art compression of raw video, our approach can reduce file size by 50-80%, while using CPU and memory resources similar to other methods.
KW - Text segmentation
KW - audit
KW - binarization
KW - monitoring
KW - screen image
KW - screen recording
UR - http://www.scopus.com/inward/record.url?scp=84874068285&partnerID=8YFLogxK
U2 - 10.1109/VCIP.2012.6410783
DO - 10.1109/VCIP.2012.6410783
M3 - Conference contribution
AN - SCOPUS:84874068285
SN - 9781467344050
T3 - 2012 IEEE Visual Communications and Image Processing, VCIP 2012
BT - 2012 IEEE Visual Communications and Image Processing, VCIP 2012
T2 - 2012 IEEE Visual Communications and Image Processing, VCIP 2012
Y2 - 27 November 2012 through 30 November 2012
ER -