A wearable motion tracker

Moiz, Fahad; Leon-Salas, Daniel; Lee, Yugyung

doi:10.1145/2221924.2221965

Cited by 2 publications

(2 citation statements)

References 14 publications

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“…al. [42] introduced and developed a wearable, multi-modality, motion capture platform, and used its inertial and ultrasonic sensors to estimate position. The focus of our work is different, on verifying liveness of a video through the consistency of its video and accelerometer data.…”

Section: Limitationsmentioning

confidence: 99%

Movee: Video Liveness Verification for Mobile Devices Using Built-In Motion Sensors

Rahman

Topkara²,

Cărbunar

2016

IEEE Trans. on Mobile Comput.

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The ubiquitous and connected nature of cameraequipped mobile devices has greatly increased the value and importance of visual information they capture. Today, broadcasting videos from camera phones uploaded by unknown users is admissible on news networks, and banking customers expect to be able to deposit checks using mobile devices. In this paper we introduce Movee, a system that addresses the fundamental question of whether the visual stream uploaded by a user has been captured live on a mobile device, and has not been tampered with by an adversary.Movee leverages the mobile device motion sensors and the intrinsic user movements during the shooting of the video. Movee exploits the observation that the movement of the scene recorded on the video stream should be related to the movement of the device simultaneously captured by the accelerometer. Contrary to existing algorithms, Movee has the unique strength of not depending on the audio track.We introduce novel attacks that focus on Movee's defenses, to fabricate acceleration data that mimics the motion observed in targeted videos. We use smartphones and wearable smart glasses to collect both genuine and attack data from 13 users. Our experiments show that Movee is able to efficiently detect human and automatically generated plagiarized videos: Movee's accuracy ranges between 68-93% on a smartphone, and between 76-91% on a Google Glass device.1536-1233 (c)

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Section: Limitationsmentioning

confidence: 99%

Movee: Video Liveness Verification for Mobile Devices Using Built-In Motion Sensors

Rahman

Topkara²,

Cărbunar

2016

IEEE Trans. on Mobile Comput.

View full text Add to dashboard Cite

show abstract

“…al. [33] introduced and developed a wearable, multi-modality, motion capture platform, and used its inertial and ultrasonic sensors to estimate position. The focus of our work is different, on verifying liveness of a video through the consistency of its video and accelerometer data.…”

Section: Related Workmentioning

confidence: 99%

Seeing is not believing

Rahman

Topkara

Cărbunar

2013

Proceedings of the 29th Annual Computer Security Applications Conference

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The visual information captured with camera-equipped mobile devices has greatly appreciated in value and importance as a result of their ubiquitous and connected nature. Today, banking customers expect to be able to deposit checks using mobile devices, and broadcasting videos from camera phones uploaded by unknown users is admissible on news networks. We present Movee, a system that addresses the fundamental question of whether the visual stream coming into a mobile app from the camera of the device can be trusted to be untampered with, live data, before it can be used for a variety of purposes.Movee is a novel approach to video liveness analysis for mobile devices. It is based on measuring the consistency between the data from the accelerometer sensor and the inferred motion from the captured video. Contrary to existing algorithms, Movee has the unique strength of not depending on the audio track. Our experiments on real user data have shown that Movee achieves 8% Equal Error Rate.

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A wearable motion tracker

Cited by 2 publications

References 14 publications

Movee: Video Liveness Verification for Mobile Devices Using Built-In Motion Sensors

Movee: Video Liveness Verification for Mobile Devices Using Built-In Motion Sensors

Seeing is not believing

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