Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Machine-assisted election auditing
EVT'07 Proceedings of the USENIX Workshop on Accurate Electronic Voting Technology
In defense of pseudorandom sample selection
EVT'08 Proceedings of the conference on Electronic voting technology
EVT'08 Proceedings of the conference on Electronic voting technology
ICDAR '09 Proceedings of the 2009 10th International Conference on Document Analysis and Recognition
Risk-limiting postelection audits: conservative P-values from common probability inequalities
IEEE Transactions on Information Forensics and Security - Special issue on electronic voting
Understanding the security properties of ballot-based verification techniques
EVT/WOTE'09 Proceedings of the 2009 conference on Electronic voting technology/workshop on trustworthy elections
Weight, weight, don't tell me: using scales to select ballots for auditing
EVT/WOTE'09 Proceedings of the 2009 conference on Electronic voting technology/workshop on trustworthy elections
An analysis of write-in marks on optical scan ballots
EVT/WOTE'11 Proceedings of the 2011 conference on Electronic voting technology/workshop on trustworthy elections
Operator-assisted tabulation of optical scan ballots
EVT/WOTE'12 Proceedings of the 2012 international conference on Electronic Voting Technology/Workshop on Trustworthy Elections
Object reading: text recognition for object recognition
ECCV'12 Proceedings of the 12th international conference on Computer Vision - Volume Part III
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Existing optical scan voting systems depend on the integrity of the scanner. If a compromised--or merely faulty--scanner reports incorrect results, there is no ready mechanism for detecting errors. While methods exist for ameliorating these risks, none of them are entirely satisfactory. We propose an alternative: a radically open system in which any observer can simultaneously and independently count the ballots for himself. Our approach, called OpenScan, combines digital video recordings of ballot sheet feeding with computer vision techniques to allow any observer with a video camera to obtain a series of ballot images that he can then process with ordinary optical scan counting software. Preliminary experimental results indicate that OpenScan produces accurate results at a manageable cost of around $1000 in hardware plus $0.0010 per ballot counted.