Camera distance from face images
Publikation: Bidrag til tidsskrift › Konferenceartikel › Forskning › fagfællebedømt
We present a method for estimating the distance between a camera and a human head in 2D images from a calibrated camera. Leading head pose estimation algorithms focus mainly on head orientation (yaw, pitch, and roll) and translations perpendicular to the camera principal axis. Our contribution is a system that can estimate head pose under large translations parallel to the camera's principal axis. Our method uses a set of exemplar 3D human heads to estimate the distance between a camera and a previously unseen head. The distance is estimated by solving for the camera pose using Effective Perspective n-Point (EPnP). We present promising experimental results using the Texas 3D Face Recognition Database.
Originalsprog | Engelsk |
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Tidsskrift | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
Udgave nummer | PART 2 |
Sider (fra-til) | 513-522 |
Antal sider | 10 |
ISSN | 0302-9743 |
DOI | |
Status | Udgivet - 2013 |
Eksternt udgivet | Ja |
Begivenhed | 9th International Symposium on Advances in Visual Computing, ISVC 2013 - Rethymnon, Crete, Grækenland Varighed: 29 jul. 2013 → 31 jul. 2013 |
Konference
Konference | 9th International Symposium on Advances in Visual Computing, ISVC 2013 |
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Land | Grækenland |
By | Rethymnon, Crete |
Periode | 29/07/2013 → 31/07/2013 |
Sponsor | BAE Systems, Intel, Ford, Hewlett-Packard, Mitsubishi Electric Research Labs |
ID: 302046971