Seeing is not believing: visual verifications through liveness analysis using mobile devices

Mahmudur Rahman, Umut Topkara, Bogdan Carbunar
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引用次数: 10

Abstract

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 un-tampered 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.
眼见为实:通过移动设备进行活体分析的视觉验证
通过配备摄像头的移动设备捕捉到的视觉信息,由于其无处不在和相互联系的特性,其价值和重要性得到了极大的赞赏。如今,银行客户期望能够使用移动设备存入支票,并且可以在新闻网络上播放未知用户上传的照相手机的视频。我们介绍了move,一个系统,它解决了一个基本问题,即从设备的摄像头进入移动应用程序的视觉流是否可以信任,在它被用于各种目的之前,它是不被篡改的,实时数据。move是一种新颖的移动设备视频活动性分析方法。它是基于测量加速度计传感器的数据与从捕获的视频推断的运动之间的一致性。与现有的算法不同,move具有不依赖音轨的独特优势。我们在真实用户数据上的实验表明,move达到了8%的相等错误率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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