Attribute-based people search in surveillance environments
Daniel A. Vaquero, Rogerio S. Feris, et al.
WACV 2009
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.
Daniel A. Vaquero, Rogerio S. Feris, et al.
WACV 2009
Conrad Albrecht, Jannik Schneider, et al.
CVPR 2025
Pavel Kisilev, Daniel Freedman, et al.
ICPR 2012
Sudeep Sarkar, Kim L. Boyer
Computer Vision and Image Understanding