Source camera attribution using stabilized video

Samet Taspinar, Manoranjan Mohanty, Nasir Memon

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Although PRNU (Photo Response Non-Uniformity)-based methods have been proposed to verify the source camera of a non-stabilized video, these methods may not be adequate for stabilized videos. The use of video stabilization has been increasing in recent years with the development of novel stabilization software and the availability of stabilization in smart-phone cameras. This paper presents a PRNU-based source camera attribution method for out-of-camera stabilized video (i.e., stabilization applied after the video is captured). The scheme can (i) automatically determine if a given video is stabilized, (ii) calculate the fingerprint from a stabilized video, and (iii) effectively correlate the fingerprint computed from a stabilized video (i.e., anonymous video) with a fingerprint computed from another stabilized or non-stabilized video (i.e., a known video). Furthermore, experimental results show that the source camera of an anonymous non-stabilized video can be verified using a fingerprint computed from a set of images.

Original languageEnglish (US)
Title of host publication8th IEEE International Workshop on Information Forensics and Security, WIFS 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509011384
DOIs
StatePublished - Jan 18 2017
Event8th IEEE International Workshop on Information Forensics and Security, WIFS 2016 - Abu Dhabi, United Arab Emirates
Duration: Dec 4 2016Dec 7 2016

Other

Other8th IEEE International Workshop on Information Forensics and Security, WIFS 2016
CountryUnited Arab Emirates
CityAbu Dhabi
Period12/4/1612/7/16

Fingerprint

attribution
video
Cameras
Stabilization
stabilization
Light sources
Attribution
Availability
Uniformity

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems and Management
  • Safety, Risk, Reliability and Quality
  • Law

Cite this

Taspinar, S., Mohanty, M., & Memon, N. (2017). Source camera attribution using stabilized video. In 8th IEEE International Workshop on Information Forensics and Security, WIFS 2016 [7823918] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/WIFS.2016.7823918

Source camera attribution using stabilized video. / Taspinar, Samet; Mohanty, Manoranjan; Memon, Nasir.

8th IEEE International Workshop on Information Forensics and Security, WIFS 2016. Institute of Electrical and Electronics Engineers Inc., 2017. 7823918.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Taspinar, S, Mohanty, M & Memon, N 2017, Source camera attribution using stabilized video. in 8th IEEE International Workshop on Information Forensics and Security, WIFS 2016., 7823918, Institute of Electrical and Electronics Engineers Inc., 8th IEEE International Workshop on Information Forensics and Security, WIFS 2016, Abu Dhabi, United Arab Emirates, 12/4/16. https://doi.org/10.1109/WIFS.2016.7823918
Taspinar S, Mohanty M, Memon N. Source camera attribution using stabilized video. In 8th IEEE International Workshop on Information Forensics and Security, WIFS 2016. Institute of Electrical and Electronics Engineers Inc. 2017. 7823918 https://doi.org/10.1109/WIFS.2016.7823918
Taspinar, Samet ; Mohanty, Manoranjan ; Memon, Nasir. / Source camera attribution using stabilized video. 8th IEEE International Workshop on Information Forensics and Security, WIFS 2016. Institute of Electrical and Electronics Engineers Inc., 2017.
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