Verification of Video Source Camera Competition (CAMCOM 2010)

Houten, Wiger van; Geradts, Zeno; Franke, Katrin; Veenman, Cor J.

doi:10.1007/978-3-642-17711-8_3

Cited by 8 publications

(5 citation statements)

References 6 publications

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“…CAMCOM2010 [17] is a contest designed to identify source YouTube videos. Two participants submitted results despite a satisfactory number of participants at first.…”

Section: Literature Reviewmentioning

confidence: 99%

A New Forensic Video Database for Source Smartphone Identification: Description and Analysis

et al. 2022

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In recent years, the field of digital imaging has made significant progress, so that today every smartphone has a built-in video camera that allows you to record high-quality video for free and without restrictions. On the other hand, rapidly growing internet technology has contributed significantly to the widespread use of digital video via web-based multimedia systems and mobile smartphone applications such as YouTube, Facebook, Twitter, WhatsApp, etc. However, as the recording and distribution of digital videos have become affordable nowadays, security issues have become threatening and spread worldwide. One of the security issues is identifying source cameras on videos. There are some new challenges that should be addressed in this area. One of the new challenges is individual source camera identification (ISCI), which focuses on identifying each device regardless of its model. The first step towards solving the problems is a popular video database recorded by modern smartphone devices, which can also be used for deep learning methods that are growing rapidly in the field of source camera identification. In this paper, a smartphone video database named Qatar University Forensic Video Database (QUFVD) is introduced. The QUFVD includes 6000 videos from 20 modern smartphone representing five brands, each brand has two models, and each model has two identical smartphone devices. This database is suitable for evaluating different techniques such as deep learning methods for video source smartphone identification and verification. To evaluate the QUFVD , a series of experiments to identify source cameras using a deep learning technique are conducted. The results show that improvements are essential for the ISCI scenario on video.

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“…CAMCOM2010 [17] is a contest designed to identify source YouTube videos. Two participants submitted results despite a satisfactory number of participants at first.…”

Section: Literature Reviewmentioning

confidence: 99%

A New Forensic Video Database for Source Smartphone Identification: Description and Analysis

et al. 2022

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“…Image is always decoded by independent slices, and then the decoded MBs (Macroblock) are reprogrammed into an image according to slice groups. So in that sense, the slice is the largest decode unit in practice [15].…”

Section: Extraction Of Video Framementioning

confidence: 99%

Video Forensic of Fragmented Video Based on H.264/AVC Video Compression Standard

Sheng¹,

Liao²,

Zhang³

et al. 2014

Proceedings of the 2014 International Conference on Mechatronics, Electronic, Industrial and Control Engineering

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Abstract-Traditional video forensics were just for complete video files, which aim at reconstructing the processing history of the video data and validating their origins or authenticity. They have obtained great achievements. However, we cannot always get complete video file in practice, sometime we only get part of it. In this paper, we came up with a method that can restore images of IDR frames from fragmented video files. After analyzing the format of MP4 and H.264/AVC Compression Standard, we proposed an algorithm to search for valid slices from fragment video files. With these slices, images of IDR frames can be restored by reconstructing sequence parameter set and picture parameter set. Test results show that images can be successfully restored in most cases except that FMO or data segmentation is adopted in the process of encoding.

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“…The challenging problem of video source identification from low-quality videos has been deeply explored by van Houten et al [40][41][42] in several works. The authors recorded videos using several different cameras, with various resolutions and bitrates.…”

Section: Prnu Based Source Identificationmentioning

confidence: 99%

An overview on video forensics

Bestagini

Fontani

Milani

et al. 2012

SIP

196

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The broad availability of tools for the acquisition and processing of multimedia signals has recently led to the concern that images and videos cannot be considered a trustworthy evidence, since they can be altered rather easily. This possibility raises the need to verify whether a multimedia content, which can be downloaded from the internet, acquired by a video surveillance system, or received by a digital TV broadcaster, is original or not. To cope with these issues, signal processing experts have been investigating effective video forensic strategies aimed at reconstructing the processing history of the video data under investigation and validating their origins. The key assumption of these techniques is that most alterations are not reversible and leave in the reconstructed signal some "footprints", which can be analyzed in order to identify the previous processing steps. This paper presents an overview of the video forensic techniques that have been proposed in the literature, focusing on the acquisition, compression, and editing operations, trying to highlight strengths and weaknesses of each solution. It also provides a review of simple processing chains that combine different operations. Anti-forensic techniques are also considered to outline the current limitations and highlight the open research issues

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Verification of Video Source Camera Competition (CAMCOM 2010)

Cited by 8 publications

References 6 publications

A New Forensic Video Database for Source Smartphone Identification: Description and Analysis

A New Forensic Video Database for Source Smartphone Identification: Description and Analysis

Video Forensic of Fragmented Video Based on H.264/AVC Video Compression Standard

An overview on video forensics

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